patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
8,578,266 | 3 | 12 | 3. The method of claim 1 , comprising providing a command language set allowing selection, viewing and other processing of the one or more portions of the first markup language file, the command language set comprising a plurality of commands for selection. | 3. The method of claim 1 , comprising providing a command language set allowing selection, viewing and other processing of the one or more portions of the first markup language file, the command language set comprising a plurality of commands for selection. 12. The method of claim 3 , wherein said command language set comprises a command for making new files in the directory structure. | 0.737903 |
9,063,581 | 12 | 14 | 12. The non-transitory computer-usable storage medium of claim 11 , where the user-encoded target length of the target string comprises a user-maintained selection time of a symbol of the sub-sequence, and where the embodied computer program code configured, when executed by a computer, for detecting, via a user input device as part of user entry of a sub-sequence of a sequence of symbols of a target string, a user-encoded target length of the target string comprises computer executable instructions configured, when executed by the computer, for: detecting, during user entry of the symbol of the sub-sequence, a user-maintained press of an input key that enters the symbol of the sub-sequence for a defined duration of time that corresponds to a defined target length; and setting the target length as the defined target length that corresponds to the defined duration of time for which the user-maintained press of the input key that enters the symbol of the sub-sequence was detected. | 12. The non-transitory computer-usable storage medium of claim 11 , where the user-encoded target length of the target string comprises a user-maintained selection time of a symbol of the sub-sequence, and where the embodied computer program code configured, when executed by a computer, for detecting, via a user input device as part of user entry of a sub-sequence of a sequence of symbols of a target string, a user-encoded target length of the target string comprises computer executable instructions configured, when executed by the computer, for: detecting, during user entry of the symbol of the sub-sequence, a user-maintained press of an input key that enters the symbol of the sub-sequence for a defined duration of time that corresponds to a defined target length; and setting the target length as the defined target length that corresponds to the defined duration of time for which the user-maintained press of the input key that enters the symbol of the sub-sequence was detected. 14. The non-transitory computer-usable storage medium of claim 12 , where the embodied computer program code configured, when executed by the computer, for setting the target length as the defined target length that corresponds to the defined duration of time for which the user-maintained press of the input key that enters the symbol of the sub-sequence was detected comprises computer executable instructions configured, when executed by the computer, for: setting the target length to a corresponding target length defined to correspond to a measured selection time of a last symbol of the sub-sequence; and where the computer program code configured, when executed by the computer, for enabling user selection of one of the eligible strings via the user input device as the target string comprises computer program code configured, when executed by the computer, for: displaying the eligible strings; prompting the user to select one of the eligible strings; detecting a selection of an eligible string; and completing the sub-sequence automatically in response to detecting the selection of the eligible string. | 0.5 |
8,185,606 | 15 | 20 | 15. A computer program product for email change tracking, the computer program product comprising a computer usable recordable type medium containing computer executable program code tangibly embodied thereon, the computer executable program code comprising: computer executable program code for receiving an email having a change tracking annotation defining an annotated portion within the email to form a received email, wherein the received email includes a set of tags comprising start and end tags defining an annotated portion, wherein the tags of the annotated portion comprise tags from a set of comment tags; computer executable program code for parsing the received email with a first parser, the first parser ignoring the annotated portion, to form a parsed first portion, wherein the tags of the annotated portion are ignored by the first parser; computer executable program code for parsing the received email with a second parser capable of parsing the annotated portion, to form a parsed annotated portion, wherein the tags of the annotated portion are parsed by the second parser; and computer executable program code for displaying the received email comprising the parsed first portion and the parsed annotated portion, wherein the parsed annotated portion includes email change tracking indicating changes in a text that occurred at each location of each text change to a user. | 15. A computer program product for email change tracking, the computer program product comprising a computer usable recordable type medium containing computer executable program code tangibly embodied thereon, the computer executable program code comprising: computer executable program code for receiving an email having a change tracking annotation defining an annotated portion within the email to form a received email, wherein the received email includes a set of tags comprising start and end tags defining an annotated portion, wherein the tags of the annotated portion comprise tags from a set of comment tags; computer executable program code for parsing the received email with a first parser, the first parser ignoring the annotated portion, to form a parsed first portion, wherein the tags of the annotated portion are ignored by the first parser; computer executable program code for parsing the received email with a second parser capable of parsing the annotated portion, to form a parsed annotated portion, wherein the tags of the annotated portion are parsed by the second parser; and computer executable program code for displaying the received email comprising the parsed first portion and the parsed annotated portion, wherein the parsed annotated portion includes email change tracking indicating changes in a text that occurred at each location of each text change to a user. 20. The computer program product of claim 15 wherein the comment tags are located in a block of text adjacent to a modified text indicating where each change occurred in the block of text. | 0.876963 |
9,015,082 | 11 | 12 | 11. The non-transitory computer readable storage medium of claim 7 , wherein the received training data set is a single data set that does not distinguish between the plurality of sensitive documents or the plurality of non-sensitive documents, the operations further comprising: using local weighted latent semantic indexing (LSI) to divide the training data set into a plurality of distinct sets of documents; identifying a first distinct set of documents as containing the plurality of sensitive documents and a second distinct set of documents as containing the plurality of non-sensitive documents; and using machine learning with the first distinct set of documents and the second distinct set of documents to generate the machine learning-based detection (MLD) profile. | 11. The non-transitory computer readable storage medium of claim 7 , wherein the received training data set is a single data set that does not distinguish between the plurality of sensitive documents or the plurality of non-sensitive documents, the operations further comprising: using local weighted latent semantic indexing (LSI) to divide the training data set into a plurality of distinct sets of documents; identifying a first distinct set of documents as containing the plurality of sensitive documents and a second distinct set of documents as containing the plurality of non-sensitive documents; and using machine learning with the first distinct set of documents and the second distinct set of documents to generate the machine learning-based detection (MLD) profile. 12. The non-transitory computer readable storage medium of claim 11 , wherein the first distinct set of documents is identified as containing the plurality of sensitive documents and the second distinct set of documents is identified as containing the plurality of non-sensitive documents based on user input. | 0.5 |
9,508,346 | 5 | 12 | 5. The method of claim 1 , wherein each audio file transcription comprises a word lattice and further comprising creating at least one confusion network form the word lattice. | 5. The method of claim 1 , wherein each audio file transcription comprises a word lattice and further comprising creating at least one confusion network form the word lattice. 12. The method of claim 5 , further comprising: evaluating the at least one confusion network on an utterance by utterance basis to determine an utterance by utterance conformity between a respective audio file and the language model; and evaluating the at least one confusion network on an overall basis to determine an overall conformity between a respective audio file and the language model. | 0.5 |
9,583,106 | 1 | 13 | 1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device. | 1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device. 13. The device of claim 1 , wherein the hardware processor is further configured to filter out background sounds that are provided as a portion of the speech input. | 0.688213 |
9,111,011 | 15 | 16 | 15. A computer-implemented method comprising: responsive to receiving a query prefix from a user; determining a user location where the query prefix was issued; identifying a first point of interest within a first predefined proximity to the user location; identifying a second point of interest within a second predefined proximity to the user location; determining a first category of the first point of interest; determining a second category of the first point of interest; identifying, using a database that maps categories to queries issued by users at locations within predefined proximities to points of interest having the first category, a first category-specific query in accordance with the first category and a second category-specific query in accordance with the second category, including: determining a first category-specific count representing a total number of times the query prefix was issued by users from user locations having the first category; determining a second category-specific count representing a total number of times the query prefix was issued by users from user locations having the second category; and providing a first category-specific query in accordance with the first category-specific count and a second category-specific query in accordance with the second category-specific count, wherein the first category-specific query includes the query prefix and the second category-specific query includes the query prefix; and providing, to the user, one or more queries including the first category-specific query and the second category-specific query as query suggestions for the query prefix. | 15. A computer-implemented method comprising: responsive to receiving a query prefix from a user; determining a user location where the query prefix was issued; identifying a first point of interest within a first predefined proximity to the user location; identifying a second point of interest within a second predefined proximity to the user location; determining a first category of the first point of interest; determining a second category of the first point of interest; identifying, using a database that maps categories to queries issued by users at locations within predefined proximities to points of interest having the first category, a first category-specific query in accordance with the first category and a second category-specific query in accordance with the second category, including: determining a first category-specific count representing a total number of times the query prefix was issued by users from user locations having the first category; determining a second category-specific count representing a total number of times the query prefix was issued by users from user locations having the second category; and providing a first category-specific query in accordance with the first category-specific count and a second category-specific query in accordance with the second category-specific count, wherein the first category-specific query includes the query prefix and the second category-specific query includes the query prefix; and providing, to the user, one or more queries including the first category-specific query and the second category-specific query as query suggestions for the query prefix. 16. The method of claim 15 , wherein a predefined proximity specifies a threshold distance between a user location where a query prefix is issued and a point of interest. | 0.739264 |
8,396,901 | 23 | 27 | 23. A computer program product having a non-transitory computer readable medium, said non-transitory computer readable medium having a computer program recorded therein for mapping an XML encoded dataset into a set of SQL tables, said computer program product comprising: computer program code for identifying at least one hierarchical structure associated with said XML encoded dataset; computer program code for converting said XML dataset associated with said identified hierarchical structure, said computer program code comprising: computer program code for determining a node element set for said identified hierarchical structure of said XML encoded dataset, wherein a node element in said node element set is a discrete level of said identified hierarchical structure of said dataset; computer program code for determining one or more nodes of said XML encoded dataset, said node being an instance of a node element; computer program code for allocating to said node a unique node identifier, and computer program code for generating an SQL node table containing one or more records, said one or more records corresponding to a respective one or more of said allocated node identifiers; wherein said XML encoded dataset includes a plurality of predefined portions of text-based data, each predefined portion of said text-based data being encoded using XML, and being associated with a plurality of attributes for organizing said predefined portions of said text-based data; and wherein said predefined portions include at least one modified and stored predefined portion encoded using XML, said modified predefined portion being associated with one or more attributes for organizing said predefined portions and said modified predefined portion of said text-based data. | 23. A computer program product having a non-transitory computer readable medium, said non-transitory computer readable medium having a computer program recorded therein for mapping an XML encoded dataset into a set of SQL tables, said computer program product comprising: computer program code for identifying at least one hierarchical structure associated with said XML encoded dataset; computer program code for converting said XML dataset associated with said identified hierarchical structure, said computer program code comprising: computer program code for determining a node element set for said identified hierarchical structure of said XML encoded dataset, wherein a node element in said node element set is a discrete level of said identified hierarchical structure of said dataset; computer program code for determining one or more nodes of said XML encoded dataset, said node being an instance of a node element; computer program code for allocating to said node a unique node identifier, and computer program code for generating an SQL node table containing one or more records, said one or more records corresponding to a respective one or more of said allocated node identifiers; wherein said XML encoded dataset includes a plurality of predefined portions of text-based data, each predefined portion of said text-based data being encoded using XML, and being associated with a plurality of attributes for organizing said predefined portions of said text-based data; and wherein said predefined portions include at least one modified and stored predefined portion encoded using XML, said modified predefined portion being associated with one or more attributes for organizing said predefined portions and said modified predefined portion of said text-based data. 27. The computer program product according to claim 23 , wherein said node includes at least one of a property, sub-node, initial content, and block content. | 0.78841 |
9,706,265 | 22 | 39 | 22. A method comprising: announcing, by a networked device residing in a private network of Internet, a networked service to a discovery service; enable performing, by the networked device, the discovery service for the private network; executing, by a client device residing in a same private network of the Internet as the networked device, a sandboxed program in a security sandbox; and automatically instantiating, by the client device, a connection between the sandboxed program and at least one of the networked device and the networked service based on: translating, through a NAT straddling both the same private network and a public network of the Internet, a private address of an announce message related to the announcement of the networked service to a public address thereof including a public IP address, addressing, from a private address of the sandboxed program, a discovery message to the discovery service, translating, through the NAT, the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, performing, through the discovery service, a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, responding, through the discovery service, with service information for the at least one of the networked device and the networked service. | 22. A method comprising: announcing, by a networked device residing in a private network of Internet, a networked service to a discovery service; enable performing, by the networked device, the discovery service for the private network; executing, by a client device residing in a same private network of the Internet as the networked device, a sandboxed program in a security sandbox; and automatically instantiating, by the client device, a connection between the sandboxed program and at least one of the networked device and the networked service based on: translating, through a NAT straddling both the same private network and a public network of the Internet, a private address of an announce message related to the announcement of the networked service to a public address thereof including a public IP address, addressing, from a private address of the sandboxed program, a discovery message to the discovery service, translating, through the NAT, the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, performing, through the discovery service, a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, responding, through the discovery service, with service information for the at least one of the networked device and the networked service. 39. The method of claim 22 , further comprising: sending, by the at least one of the networked device and the networked service, a number of periodic keep-alive messages to the discovery service. | 0.891667 |
5,534,861 | 1 | 2 | 1. A computer program product for use with a computer-implemented system for compressing input data consisting of sequences of source symbols selected from a source alphabet to form output data consisting of sequences of code symbols selected from a code alphabet according to a static dictionary stored in memory, said dictionary representing a static parse-tree having nodes representing said code symbols, said nodes being linked into paths representing said source symbol sequences, said computer program product comprising: a recording medium; means, recorded on said recording medium, for directing said computer-implemented system to repeatedly perform the steps of determining a source symbol sequence from said input data, adding at least one node to said parse-tree responsive to said source symbol sequence, and assigning a use count value to said at least one node responsive to the number of said source symbol sequence occurrences; and means, recorded on said recording medium, for directing said computer-implemented system to reduce said parse-tree to a first predetermined plurality of nodes by repeatedly deleting from said parse-tree one or more childless nodes having a use count value less than a predetermined use count value threshold. | 1. A computer program product for use with a computer-implemented system for compressing input data consisting of sequences of source symbols selected from a source alphabet to form output data consisting of sequences of code symbols selected from a code alphabet according to a static dictionary stored in memory, said dictionary representing a static parse-tree having nodes representing said code symbols, said nodes being linked into paths representing said source symbol sequences, said computer program product comprising: a recording medium; means, recorded on said recording medium, for directing said computer-implemented system to repeatedly perform the steps of determining a source symbol sequence from said input data, adding at least one node to said parse-tree responsive to said source symbol sequence, and assigning a use count value to said at least one node responsive to the number of said source symbol sequence occurrences; and means, recorded on said recording medium, for directing said computer-implemented system to reduce said parse-tree to a first predetermined plurality of nodes by repeatedly deleting from said parse-tree one or more childless nodes having a use count value less than a predetermined use count value threshold. 2. The computer program product of claim 1 further comprising: means, recorded on said recording medium, for directing said computer-implemented system to combine with its parent node at least one childless node having a single-child parent node for which said use count differs by no more than one from said use count value for said at least one childless node, thereby forming a new childless node. | 0.5 |
8,447,607 | 1 | 10 | 1. A device for processing natural language inputs, comprising one or more processors configured to: receive a multi-modal natural language input from a user, the multi-modal natural language input including a natural language utterance and a non-speech input; generate a non-speech transcription from the non-speech input; identify the user who provided the multi-modal natural language input; generate a speech-based transcription based on a cognitive model associated with the user, wherein the cognitive model includes information on one or more prior interactions between the user and the device; generate a merged transcription from the speech-based transcription and the non-speech transcription; identify, from among a plurality of entries that are in a context stack and that are each indicative of context, an entry in the context stack that matches information in the merged transcription; identify a domain agent associated with the entry in the context stack; determine a request based on the merged transcription; and communicate the request to the domain agent, wherein the domain agent is configured to generate a response to the user. | 1. A device for processing natural language inputs, comprising one or more processors configured to: receive a multi-modal natural language input from a user, the multi-modal natural language input including a natural language utterance and a non-speech input; generate a non-speech transcription from the non-speech input; identify the user who provided the multi-modal natural language input; generate a speech-based transcription based on a cognitive model associated with the user, wherein the cognitive model includes information on one or more prior interactions between the user and the device; generate a merged transcription from the speech-based transcription and the non-speech transcription; identify, from among a plurality of entries that are in a context stack and that are each indicative of context, an entry in the context stack that matches information in the merged transcription; identify a domain agent associated with the entry in the context stack; determine a request based on the merged transcription; and communicate the request to the domain agent, wherein the domain agent is configured to generate a response to the user. 10. The device of claim 1 , wherein the one or more processors are configured to synchronize the context stack with a context stack of another device. | 0.767081 |
9,053,179 | 1 | 5 | 1. A method for providing a citation network viewer, the method comprising: receiving a plurality of documents, wherein each document of the plurality of documents comprises a citation and discusses at least one issue, and relationships between individual ones of the plurality of documents as defined by the citations form a multi-dimensional citation network; identifying at least a portion of citations, reasons-for-citing and headnotes associated with the identified citations from individual sentences of the plurality of documents; converting the identified reasons-for-citing and the identified headnotes in at least some of the documents of the plurality of documents into vectors; establishing one or more semantic links between individual documents of the plurality of documents by pairing starting reasons-for-citing in citing documents with cited reasons-for-citing and headnotes in cited documents; and creating a plurality of metadata files based at least in part on the plurality of documents, the citations and the semantic links; creating a sub-network of citations of documents that corresponds to a specific issue from the metadata files of the documents forming the multi-dimensional network; and providing for display an interactive user interface representing the sub-network the interactive user interface comprising a plurality of icons, wherein: each icon represents an individual reason-for-citing or headnote within an individual document; each icon is linked to another icon by a line, the line indicating only a citation between documents represented by the linked icons; and the plurality of icons are hierarchically arranged. | 1. A method for providing a citation network viewer, the method comprising: receiving a plurality of documents, wherein each document of the plurality of documents comprises a citation and discusses at least one issue, and relationships between individual ones of the plurality of documents as defined by the citations form a multi-dimensional citation network; identifying at least a portion of citations, reasons-for-citing and headnotes associated with the identified citations from individual sentences of the plurality of documents; converting the identified reasons-for-citing and the identified headnotes in at least some of the documents of the plurality of documents into vectors; establishing one or more semantic links between individual documents of the plurality of documents by pairing starting reasons-for-citing in citing documents with cited reasons-for-citing and headnotes in cited documents; and creating a plurality of metadata files based at least in part on the plurality of documents, the citations and the semantic links; creating a sub-network of citations of documents that corresponds to a specific issue from the metadata files of the documents forming the multi-dimensional network; and providing for display an interactive user interface representing the sub-network the interactive user interface comprising a plurality of icons, wherein: each icon represents an individual reason-for-citing or headnote within an individual document; each icon is linked to another icon by a line, the line indicating only a citation between documents represented by the linked icons; and the plurality of icons are hierarchically arranged. 5. The method as claimed in claim 1 , wherein the computer program product further comprises executable instructions that, when read and executed by the computer, causes the computer to: perform a depth-first search in the citation network represented by the established semantic links between documents; and retrieve forward-chained and backward-chained reasons-for-citing and headnotes based on a starting reason-for-citing representing a specified citation. | 0.5 |
6,026,358 | 13 | 15 | 13. A neural network comprising: a neuron device network having a data input layer, a hidden layer connected to said data input layer, and an output layer connected to said hidden layer, said output layer comprising a first output layer and a second output layer; learning means in said neuron device network for learning about data having a plurality of first vector rows representing a definite meaning, said learning means inputting said plurality of first vector rows to said data input layer, inputting second vector rows as a first instructor signal to said first output layer and inputting said definite meaning as a second instructor signal to said second output layer; inputting means for inputting said plurality of first vector rows to said data input layer of said neuron device network; and outputting means for outputting output signals of said second output layer based on input of said plurality of first vector rows by said inputting means. | 13. A neural network comprising: a neuron device network having a data input layer, a hidden layer connected to said data input layer, and an output layer connected to said hidden layer, said output layer comprising a first output layer and a second output layer; learning means in said neuron device network for learning about data having a plurality of first vector rows representing a definite meaning, said learning means inputting said plurality of first vector rows to said data input layer, inputting second vector rows as a first instructor signal to said first output layer and inputting said definite meaning as a second instructor signal to said second output layer; inputting means for inputting said plurality of first vector rows to said data input layer of said neuron device network; and outputting means for outputting output signals of said second output layer based on input of said plurality of first vector rows by said inputting means. 15. The neural network according to claim 13, wherein said data input layer, said hidden layer and said second output layer each have connection weights between respective neuron devices. | 0.748656 |
8,510,321 | 1 | 10 | 1. An apparatus for accessing and managing a relational database, said apparatus comprising: a processor; an arrangement for querying a relational database; and an arrangement for accessing semantically relevant query results from the relational database, said accessing arrangement configured to: access at least one ontology; extract domain knowledge from at least one ontology; and employ the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein said accessing arrangement acts to: apply a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and rank results obtained through the query generalization strategy based on a number generalizations performed. | 1. An apparatus for accessing and managing a relational database, said apparatus comprising: a processor; an arrangement for querying a relational database; and an arrangement for accessing semantically relevant query results from the relational database, said accessing arrangement configured to: access at least one ontology; extract domain knowledge from at least one ontology; and employ the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein said accessing arrangement acts to: apply a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and rank results obtained through the query generalization strategy based on a number generalizations performed. 10. The apparatus according to claim 1 , further comprising a wrapper arrangement which acts to translate data from the relational database into a predetermined format for said accessing arrangement. | 0.732527 |
7,602,309 | 1 | 2 | 1. A method of managing data stored in a electronic device, the method comprising: electronically identifying a user input written on a display of the electronic device as a written user direction to transfer data displayed on the electronic device, the written user input defining at least one alphanumeric character; determining a desired memory storage location for the data displayed on the electronic device responsive to the written user direction, wherein the desired memory storage location corresponds to the alphanumeric character defined by the written user input; and transferring the data displayed on the electronic device to the desired memory storage location responsive to the determination. | 1. A method of managing data stored in a electronic device, the method comprising: electronically identifying a user input written on a display of the electronic device as a written user direction to transfer data displayed on the electronic device, the written user input defining at least one alphanumeric character; determining a desired memory storage location for the data displayed on the electronic device responsive to the written user direction, wherein the desired memory storage location corresponds to the alphanumeric character defined by the written user input; and transferring the data displayed on the electronic device to the desired memory storage location responsive to the determination. 2. The method of claim 1 , further comprising: receiving the written user input comprising writing the at least one alphanumeric character and/or a symbol on the display of the electronic device via a stylus. | 0.704545 |
8,359,331 | 9 | 10 | 9. A machine readable non-transitory storage medium storing executable program instructions which when executed by a data processing system cause the data processing system to perform a method of processing data, the method comprising: receiving an input which represents a search query, the search query comprising a single prefix character followed by at least one word and further includes a parameter; automatically interpreting the search query, the interpreting comprising linking the single prefix character followed by at least one word and the parameter according to a logical combination definition, wherein the logical combination definition is at least partly based on a data type of the parameter; performing, in response to the input, a prefix matching search through indexed content of a plurality of different files stored in an index database and metadata, stored in a metadata database, for the plurality of different files, wherein a plurality of importers or exporters caused metadata to be added to the metadata database and wherein matching metadata or content begins at the single prefix character and is followed by the at least one word. | 9. A machine readable non-transitory storage medium storing executable program instructions which when executed by a data processing system cause the data processing system to perform a method of processing data, the method comprising: receiving an input which represents a search query, the search query comprising a single prefix character followed by at least one word and further includes a parameter; automatically interpreting the search query, the interpreting comprising linking the single prefix character followed by at least one word and the parameter according to a logical combination definition, wherein the logical combination definition is at least partly based on a data type of the parameter; performing, in response to the input, a prefix matching search through indexed content of a plurality of different files stored in an index database and metadata, stored in a metadata database, for the plurality of different files, wherein a plurality of importers or exporters caused metadata to be added to the metadata database and wherein matching metadata or content begins at the single prefix character and is followed by the at least one word. 10. The machine readable non-transitory storage medium of claim 9 wherein at least one of dot (“.”) and dash (“-”) are matched as part of the prefix matching search. | 0.5 |
8,200,793 | 1 | 8 | 1. A method comprising: embedding a control mark within an electronic document created by a document word processor, wherein the control mark remains embedded in the electronic document after changing a body of the electronic document with the document word processor; wherein the control mark cannot be changed by or removed with the document word processor; and wherein the control mark includes an encrypted check sum configured to self-authenticate or self-validate the electronic document; detecting at least one packet containing the electronic document transmitted over a network; making a determination that the electronic document has been changed in response to detecting the control mark in the electronic document contained in the at least one packet; and blocking access to the electronic document in response to the determination. | 1. A method comprising: embedding a control mark within an electronic document created by a document word processor, wherein the control mark remains embedded in the electronic document after changing a body of the electronic document with the document word processor; wherein the control mark cannot be changed by or removed with the document word processor; and wherein the control mark includes an encrypted check sum configured to self-authenticate or self-validate the electronic document; detecting at least one packet containing the electronic document transmitted over a network; making a determination that the electronic document has been changed in response to detecting the control mark in the electronic document contained in the at least one packet; and blocking access to the electronic document in response to the determination. 8. The method of claim 1 wherein the at least one packet is transmitted in response to an FTP download. | 0.801923 |
8,516,585 | 1 | 20 | 1. A computer-implemented method for detecting malicious software agents, the method comprising: (a) constructing an association based on a plurality of failed queries for domain names sent to one or more domain-name servers by a plurality of hosts during a time period; (b) deriving, from the association, one or more candidate clusters of hosts; (c) determining, for each candidate cluster and for each of a plurality of time intervals during the time period, a number of new domain names appearing in the failed queries of the candidate cluster during the time interval; (d) determining, for each candidate cluster, a freshness metric based on the numbers of new domain names for the plurality of time intervals in the time period; and (e) detecting one or more malicious software agents on the hosts based on the one or more freshness metrics. | 1. A computer-implemented method for detecting malicious software agents, the method comprising: (a) constructing an association based on a plurality of failed queries for domain names sent to one or more domain-name servers by a plurality of hosts during a time period; (b) deriving, from the association, one or more candidate clusters of hosts; (c) determining, for each candidate cluster and for each of a plurality of time intervals during the time period, a number of new domain names appearing in the failed queries of the candidate cluster during the time interval; (d) determining, for each candidate cluster, a freshness metric based on the numbers of new domain names for the plurality of time intervals in the time period; and (e) detecting one or more malicious software agents on the hosts based on the one or more freshness metrics. 20. The method of claim 1 , wherein step (d) comprises: (d1) comparing, for each of one or more time intervals, domain names queried during said each time interval with domain names queried prior to that time interval; and (d2) identifying, as new domain names, one or more domain names queried during the time interval but not prior to the time interval. | 0.772436 |
8,095,581 | 2 | 7 | 2. A computer-implemented patent portfolio analysis method comprising: retrieving patent information from a database, wherein the patent information is from a plurality of patent documents; analyzing said patent information to generate at least one eigenspace category model; and applying said category model to said patent information to select from said patent information a subset that fits said model and storing said subset in a computer-readable dataset, wherein said patent information includes claim text information to be analyzed and wherein said analyzing step includes: defining an eigenspace representing a training population of training claims each training claim having associated training text; representing at least a portion of said training claims in said eigenspace and associating a predefined category with each training claim in said eigenspace; and projecting the claim text information to be analyzed into said eigenspace and associating with said projected claim text the predefined category of the training claim to which said projected claim text is closest within the eigenspace. | 2. A computer-implemented patent portfolio analysis method comprising: retrieving patent information from a database, wherein the patent information is from a plurality of patent documents; analyzing said patent information to generate at least one eigenspace category model; and applying said category model to said patent information to select from said patent information a subset that fits said model and storing said subset in a computer-readable dataset, wherein said patent information includes claim text information to be analyzed and wherein said analyzing step includes: defining an eigenspace representing a training population of training claims each training claim having associated training text; representing at least a portion of said training claims in said eigenspace and associating a predefined category with each training claim in said eigenspace; and projecting the claim text information to be analyzed into said eigenspace and associating with said projected claim text the predefined category of the training claim to which said projected claim text is closest within the eigenspace. 7. The method of claim 2 wherein a label associated with the category model is predetermined. | 0.881378 |
9,251,250 | 3 | 4 | 3. The method of claim 1 , wherein each vocabulary usage in the training data corresponds to a dialect. | 3. The method of claim 1 , wherein each vocabulary usage in the training data corresponds to a dialect. 4. The method of claim 3 , further comprising: using the model to perform dialect estimation. | 0.5 |
9,355,178 | 10 | 11 | 10. The method of claim 4 , wherein the supplemental information comprises a link for automatically executing a second search query related to the first search query. | 10. The method of claim 4 , wherein the supplemental information comprises a link for automatically executing a second search query related to the first search query. 11. The method of claim 10 , wherein a term of the second search query is input by a user. | 0.545455 |
8,070,774 | 1 | 3 | 1. An anchor assembly comprising: an anchor body; an anchor head including a first arm and a second arm extending substantially parallel to one another and away from the anchor body, the first arm and the second arm separated by a gap; a shaft connected to the first arm and the second arm across the gap; a saddle having a longitudinal bore, a transverse bore which intersects the longitudinal bore, and a member capture opening adapted to receive a member wherein the member capture opening intersects the longitudinal bore; said transverse bore of said saddle being mounted about said shaft such that the saddle can move relative to the anchor head; a set screw received in said longitudinal bore of said saddle and adapted to lock the member in said member capture opening of said saddle; and said saddle including reinforced walls that prevent said saddle splaying when said set screw locks the member in said member capture opening of said saddle. | 1. An anchor assembly comprising: an anchor body; an anchor head including a first arm and a second arm extending substantially parallel to one another and away from the anchor body, the first arm and the second arm separated by a gap; a shaft connected to the first arm and the second arm across the gap; a saddle having a longitudinal bore, a transverse bore which intersects the longitudinal bore, and a member capture opening adapted to receive a member wherein the member capture opening intersects the longitudinal bore; said transverse bore of said saddle being mounted about said shaft such that the saddle can move relative to the anchor head; a set screw received in said longitudinal bore of said saddle and adapted to lock the member in said member capture opening of said saddle; and said saddle including reinforced walls that prevent said saddle splaying when said set screw locks the member in said member capture opening of said saddle. 3. The anchor assembly of claim 1 wherein said saddle has flat outer walls. | 0.847561 |
9,264,784 | 9 | 14 | 9. A recommendation system comprising: one or more communication interfaces; one or more memories that store instructions; and one or more processors to execute the instructions to: obtain, via at least one of the one or more communication interfaces, program historical data associated with users that each receive one or more programs via one or more channels of a program delivery network that provides a program service to which the users belong; obtain, via at least one of the one or more communication interfaces, social network data associated with the users from social network sites to which the users belong, wherein the social network data includes a social graph, communication data pertaining to communications between the users via a communication network that provides a communication service to which the users belong, wherein the communication service includes a mobile phone service and a messaging service, and the communication data includes mobile phone calls, and user profile information pertaining to the users; calculate based on the social network data, the communication data, and the user profile information, a social similarity value that indicates a social similarity between one of the users and other users; calculate based on the program historical data, a channel-interest similarity value that indicates a common interest between the one of the users and the other users in relation to the one or more channels used by the users to receive the one or more programs; calculate based on the social similarity value and the channel-interest similarity value, a similarity index value that indicates a similarity between the one of the users and the other users; calculate based on the program historical data a program regularity value, for each program, that indicates a regularity of consumption of each program over a time period; calculate based on the program regularity value, a program weight value, for each program, that indicates a priority value; calculate based on the program historical data, a stay-time, for each channel, that indicates a time period each of the users remained on each channel; calculate based on each program weight value, each stay-time, and each similarity index value, a channel weight for each channel; and select based on each channel weight, one or more channels to recommend to at least one of the users. | 9. A recommendation system comprising: one or more communication interfaces; one or more memories that store instructions; and one or more processors to execute the instructions to: obtain, via at least one of the one or more communication interfaces, program historical data associated with users that each receive one or more programs via one or more channels of a program delivery network that provides a program service to which the users belong; obtain, via at least one of the one or more communication interfaces, social network data associated with the users from social network sites to which the users belong, wherein the social network data includes a social graph, communication data pertaining to communications between the users via a communication network that provides a communication service to which the users belong, wherein the communication service includes a mobile phone service and a messaging service, and the communication data includes mobile phone calls, and user profile information pertaining to the users; calculate based on the social network data, the communication data, and the user profile information, a social similarity value that indicates a social similarity between one of the users and other users; calculate based on the program historical data, a channel-interest similarity value that indicates a common interest between the one of the users and the other users in relation to the one or more channels used by the users to receive the one or more programs; calculate based on the social similarity value and the channel-interest similarity value, a similarity index value that indicates a similarity between the one of the users and the other users; calculate based on the program historical data a program regularity value, for each program, that indicates a regularity of consumption of each program over a time period; calculate based on the program regularity value, a program weight value, for each program, that indicates a priority value; calculate based on the program historical data, a stay-time, for each channel, that indicates a time period each of the users remained on each channel; calculate based on each program weight value, each stay-time, and each similarity index value, a channel weight for each channel; and select based on each channel weight, one or more channels to recommend to at least one of the users. 14. The recommendation system of claim 9 , wherein when calculating the channel weight, at least one of the one or more processors to execute the instructions to: calculate the channel weight based on an expression: W=w*Σ i=1 N (Stay_time(U i )*S i ), wherein w is the program regularity value, Stay_time is a time user U i stays on a channel, S i is the similarity index value between the one of the users and one of the other users U i and W is the channel weight. | 0.749731 |
9,269,028 | 8 | 9 | 8. The method of claim 7 , wherein determining the character similarity index for the second input sting comprises determining if each key in the second input string is present in the first input string, and, for each individual key that is not present in the first input string, adding a predetermined score to the character similarity index for the second input string. | 8. The method of claim 7 , wherein determining the character similarity index for the second input sting comprises determining if each key in the second input string is present in the first input string, and, for each individual key that is not present in the first input string, adding a predetermined score to the character similarity index for the second input string. 9. The method of claim 8 , comprising selecting a greater of the character similarity index for the first input sting and the character similarity index for the second input sting as the string similarity index. | 0.5 |
7,536,391 | 9 | 12 | 9. A method for URL virtualization to provide a contextually relevant URL to a requesting agent, the method comprising: receiving a request for content hosted by a target server from the requesting agent, wherein the request includes a non-contextual URL; reading request header parameters in order to select a version of the requested content; accessing a URL storage area to determine that the non-contextual URL maps to a contextual URL, wherein the contextual URL is more contextually relevant and more human-readable than the non-contextual URL and wherein the URL storage area comprises a lookup table for matching the contextual URL to be supplied instead of the non-contextual URL; determining whether the contextual URL is a server-side transfer or a server-side redirect, wherein in a server-side redirect at least one of the non-contextual URL and contextual URL is mapped to an alternative URL; if the contextual URL is a server-side transfer, sending the content to the user browser for display and sending the contextual URL to the user browser for display in the user browser's address bar; and if the contextual URL is a server-side redirect, sending the content to the user browser for display and sending the alternative URL for display in the user browser's address bar. | 9. A method for URL virtualization to provide a contextually relevant URL to a requesting agent, the method comprising: receiving a request for content hosted by a target server from the requesting agent, wherein the request includes a non-contextual URL; reading request header parameters in order to select a version of the requested content; accessing a URL storage area to determine that the non-contextual URL maps to a contextual URL, wherein the contextual URL is more contextually relevant and more human-readable than the non-contextual URL and wherein the URL storage area comprises a lookup table for matching the contextual URL to be supplied instead of the non-contextual URL; determining whether the contextual URL is a server-side transfer or a server-side redirect, wherein in a server-side redirect at least one of the non-contextual URL and contextual URL is mapped to an alternative URL; if the contextual URL is a server-side transfer, sending the content to the user browser for display and sending the contextual URL to the user browser for display in the user browser's address bar; and if the contextual URL is a server-side redirect, sending the content to the user browser for display and sending the alternative URL for display in the user browser's address bar. 12. The method of claim 9 , further comprising providing the contextual URL without storing an associated physical file. | 0.5 |
8,413,069 | 4 | 5 | 4. The method of claim 1 , wherein said selection of a first character shape is received as an input to a mobile telephone, and wherein said steps of displaying are performed using a display of said mobile telephone. | 4. The method of claim 1 , wherein said selection of a first character shape is received as an input to a mobile telephone, and wherein said steps of displaying are performed using a display of said mobile telephone. 5. The method of claim 4 , wherein at least some character shapes available for selection are selected using an input key of said mobile telephone. | 0.5 |
8,473,507 | 20 | 21 | 20. The computer-implemented method of claim 19 , wherein the at least one suggestion engine comprises at least one of a date suggestion engine, a mailbox suggestion engine, and a search suggestion engine. | 20. The computer-implemented method of claim 19 , wherein the at least one suggestion engine comprises at least one of a date suggestion engine, a mailbox suggestion engine, and a search suggestion engine. 21. The computer-implemented method of claim 20 , wherein each suggestion engine generates suggestions with different scopes. | 0.5 |
9,853,818 | 32 | 33 | 32. The system as recited in claim 1 , further comprising a presentation authority configured to provide to the signing party a facsimile of the to be signed electronic document. | 32. The system as recited in claim 1 , further comprising a presentation authority configured to provide to the signing party a facsimile of the to be signed electronic document. 33. The system as recited in claim 32 , wherein the presentation authority operates under at least one of a plurality of operational policies and procedures of the presentation authority. | 0.683051 |
6,061,654 | 27 | 29 | 27. The apparatus according to claim 22, wherein the first arrangement of character recognition probabilities and the constrained arrangement of character recognition probabilities are each arranged as at least one confusion matrix. | 27. The apparatus according to claim 22, wherein the first arrangement of character recognition probabilities and the constrained arrangement of character recognition probabilities are each arranged as at least one confusion matrix. 29. The apparatus according to claim 27, wherein the at least one confusion matrix corresponds to a plurality of confusion matrices including at least one confusion matrix corresponding to alphabetical letters only, at least one confusion matrix corresponding to numbers only, and at least one confusion matrix corresponding to a combination of alphabetical letters and numbers. | 0.5 |
7,533,023 | 11 | 14 | 11. The speech processing system of claim 8 wherein the intermediary speech processor is further storing the transformed customized speech parameters in a data structure associated with the network environment. | 11. The speech processing system of claim 8 wherein the intermediary speech processor is further storing the transformed customized speech parameters in a data structure associated with the network environment. 14. The speech processing system of claim 11 wherein the data structure resides in a data store on the third computing device. | 0.585526 |
7,546,465 | 12 | 13 | 12. The method of claim 11 , further comprising: receiving the tagged data; decrypting the tagged data; and converting the tagged data into a text message that complies with the XML format. | 12. The method of claim 11 , further comprising: receiving the tagged data; decrypting the tagged data; and converting the tagged data into a text message that complies with the XML format. 13. The method of claim 12 , further comprising displaying the text message on a display device. | 0.652174 |
9,250,711 | 1 | 3 | 1. A method of enabling input into a handheld electronic device comprising: detecting an ambiguous character-string input that comprises a current character input and a previous character input; generating a plurality of character permutations of the ambiguous character-string input, at least one of the character permutations being a potential artificial variant that is neither a prefix of a word object nor is identical to a word object; outputting at least one of the character permutations other than the potential artificial variant; determining that the potential artificial variant has been displayed during a current session; based on the determination that the potential artificial variant has been displayed during a current session, outputting a displayed artificial variant as a representation of the potential artificial variant, wherein the displayed artificial variant is outputted at a position of relatively lower priority than at least one of the outputted character permutations; determining that the displayed artificial variant is not selected; and based on the determination that the displayed artificial variant is not selected, suppressing from being output an offspring artificial variant of the unselected artificial variant when a next character input associated with the ambiguous character-string is detected. | 1. A method of enabling input into a handheld electronic device comprising: detecting an ambiguous character-string input that comprises a current character input and a previous character input; generating a plurality of character permutations of the ambiguous character-string input, at least one of the character permutations being a potential artificial variant that is neither a prefix of a word object nor is identical to a word object; outputting at least one of the character permutations other than the potential artificial variant; determining that the potential artificial variant has been displayed during a current session; based on the determination that the potential artificial variant has been displayed during a current session, outputting a displayed artificial variant as a representation of the potential artificial variant, wherein the displayed artificial variant is outputted at a position of relatively lower priority than at least one of the outputted character permutations; determining that the displayed artificial variant is not selected; and based on the determination that the displayed artificial variant is not selected, suppressing from being output an offspring artificial variant of the unselected artificial variant when a next character input associated with the ambiguous character-string is detected. 3. The method of claim 1 , further comprising: making a determination that at least a portion of the potential artificial variant corresponds with an N-gram object associated with a frequency object having a frequency value above a predetermined threshold. | 0.659574 |
6,101,492 | 20 | 21 | 20. The method of claim 19, wherein the step of derivational generation further includes filtering candidate words which do not appear in the dictionary against the disambiguated corpus, and placing in the expanded corpus candidate words which appear in the disambiguated corpus. | 20. The method of claim 19, wherein the step of derivational generation further includes filtering candidate words which do not appear in the dictionary against the disambiguated corpus, and placing in the expanded corpus candidate words which appear in the disambiguated corpus. 21. The method of claim 20, wherein the metagrammar includes type 1 variant metarules extract syntactic transformations which have contributed to the generation of the variant and type 2 variant metarules extract syntactic and morphological transformations which have contributed to the generation of the variant. | 0.5 |
6,076,086 | 1 | 3 | 1. An associate document retrieving apparatus that retrieves a document related to an inputted retrieval condition, comprising: a document information storing element that associates each of a plurality of documents with a keyword extracted from the document and stores the associated documents; a retrieval expression obtaining element that retrieves a retrieval expression; a number of documents calculating element that specifies a plurality of objective keywords from within the extracted keywords stored in the document information storing element, and calculating a first number of all the associated documents, a second number of documents, within the associated documents, matching the retrieval expression, a third number of documents, within the associated documents, containing each of the objective keywords and matching the retrieval expression, and a fourth number of documents, within the associated documents, containing each of the objective keywords; a degree of similarity determining element that determines a degree of similarity between the retrieval expression and each of the objective keywords based on a relationship between the first number, the second number, the third number and the fourth number for each of the objective keywords; and a degree of association determining element that obtains associate document information of a document containing any of the objective keywords as the extracted keyword, and determines a degree of association between the retrieval expression and each of the documents stored in the document information storing element based on the degree of similarity for each of the objective keywords obtained by the degree of similarity determining element and the associate document information. | 1. An associate document retrieving apparatus that retrieves a document related to an inputted retrieval condition, comprising: a document information storing element that associates each of a plurality of documents with a keyword extracted from the document and stores the associated documents; a retrieval expression obtaining element that retrieves a retrieval expression; a number of documents calculating element that specifies a plurality of objective keywords from within the extracted keywords stored in the document information storing element, and calculating a first number of all the associated documents, a second number of documents, within the associated documents, matching the retrieval expression, a third number of documents, within the associated documents, containing each of the objective keywords and matching the retrieval expression, and a fourth number of documents, within the associated documents, containing each of the objective keywords; a degree of similarity determining element that determines a degree of similarity between the retrieval expression and each of the objective keywords based on a relationship between the first number, the second number, the third number and the fourth number for each of the objective keywords; and a degree of association determining element that obtains associate document information of a document containing any of the objective keywords as the extracted keyword, and determines a degree of association between the retrieval expression and each of the documents stored in the document information storing element based on the degree of similarity for each of the objective keywords obtained by the degree of similarity determining element and the associate document information. 3. The associate document retrieving apparatus as set forth in claim 1, wherein the degree of similarity determining element uses the extended t-score method defined by equation (2) to determine the degree of similarity between the retrieval expression and each of the objective keywords: EQU extended t-score=.alpha.[(.alpha..gamma.-.beta..delta.)/(.beta..delta.)](2) wherein .alpha., .beta., .gamma. and .delta. are the first number, the second number, the third number and the fourth number for each of the objective keywords, respectively. | 0.708378 |
8,612,426 | 1 | 15 | 1. A method of arranging media files for ethnographic research, comprising: storing in a database a plurality of electronic media files each including a digital photograph or a video clip of an interview of a human participant being photographed or video-recorded under observation or questioning by a researcher in connection with a market research study; using a controller, associating with each of at least some of the electronic media files one or more distinct interpretive tags, each of the interpretive tags being a data element stored in the database and indicative of an observed behavioral, attitudinal, or emotive characteristic of the human participant; receiving, using the controller, (a) a selection of at least a selected one of the interpretive tags or (b) a query that is run on the database including the interpretive tags; producing a search result responsive to the receiving, the search result including a subset of the electronic media files, each of at least some of the subset of electronic media files being associated with at least one of the interpretive tags or with the selected one of the interpretive tags; causing to be displayed on a display device a representation of the search result as a plurality of thumbnail images, each of the thumbnail images corresponding to a digital photograph or a video clip of corresponding ones of the subset of the electronic media files; and causing to be displayed on the display device a plurality of related tags associated with the subset of electronic media files, wherein at least one of the related tags includes an interpretive tag. | 1. A method of arranging media files for ethnographic research, comprising: storing in a database a plurality of electronic media files each including a digital photograph or a video clip of an interview of a human participant being photographed or video-recorded under observation or questioning by a researcher in connection with a market research study; using a controller, associating with each of at least some of the electronic media files one or more distinct interpretive tags, each of the interpretive tags being a data element stored in the database and indicative of an observed behavioral, attitudinal, or emotive characteristic of the human participant; receiving, using the controller, (a) a selection of at least a selected one of the interpretive tags or (b) a query that is run on the database including the interpretive tags; producing a search result responsive to the receiving, the search result including a subset of the electronic media files, each of at least some of the subset of electronic media files being associated with at least one of the interpretive tags or with the selected one of the interpretive tags; causing to be displayed on a display device a representation of the search result as a plurality of thumbnail images, each of the thumbnail images corresponding to a digital photograph or a video clip of corresponding ones of the subset of the electronic media files; and causing to be displayed on the display device a plurality of related tags associated with the subset of electronic media files, wherein at least one of the related tags includes an interpretive tag. 15. The method of claim 1 , wherein others of the electronic media files are not associated with any interpretative tag. | 0.913169 |
6,112,173 | 1 | 9 | 1. A pattern recognition device comprising: a catalog of a plurality of items of standard data each made up of a plurality of consecutive standard elements, said plurality of items of standard data having a predetermined correspondence to prescribed recognition data; a predetermined tree structure of data, said tree structure having a root node and a plurality of subordinate nodes, each said subordinate node corresponding to one of said standard elements; said plurality of subordinate nodes being linked by a number of parent nodes, said number of parent nodes being smaller than a number of said subordinate nodes, said parent nodes each corresponding, on average, to a plurality of mutually similar ones of said standard elements; parent distance calculating means for calculating respective parent node distances of similarity for each of a plurality of recognition elements included in inputted recognition data; parent node selecting means for selecting ones of said parent nodes based on a magnitude of said respective parent node distances of similarity; subordinate distance calculating means for calculating respective subordinate node distances of similarity for each of said recognition elements only for ones of said subordinate nodes linked to said selected parent nodes; distance storage means for storing only once, in order, at predetermined positions, said respective parent node distances of similarity, and for storing, in order, at other predetermined positions, only said respective subordinate node distances of similarity for said subordinate nodes of said selected parent nodes; and means for determining a recognition result based on said stored distances. | 1. A pattern recognition device comprising: a catalog of a plurality of items of standard data each made up of a plurality of consecutive standard elements, said plurality of items of standard data having a predetermined correspondence to prescribed recognition data; a predetermined tree structure of data, said tree structure having a root node and a plurality of subordinate nodes, each said subordinate node corresponding to one of said standard elements; said plurality of subordinate nodes being linked by a number of parent nodes, said number of parent nodes being smaller than a number of said subordinate nodes, said parent nodes each corresponding, on average, to a plurality of mutually similar ones of said standard elements; parent distance calculating means for calculating respective parent node distances of similarity for each of a plurality of recognition elements included in inputted recognition data; parent node selecting means for selecting ones of said parent nodes based on a magnitude of said respective parent node distances of similarity; subordinate distance calculating means for calculating respective subordinate node distances of similarity for each of said recognition elements only for ones of said subordinate nodes linked to said selected parent nodes; distance storage means for storing only once, in order, at predetermined positions, said respective parent node distances of similarity, and for storing, in order, at other predetermined positions, only said respective subordinate node distances of similarity for said subordinate nodes of said selected parent nodes; and means for determining a recognition result based on said stored distances. 9. The pattern recognition device as set forth in claim 1, wherein said recognition data inputted to said data input means are made up of speech signals and said standard data catalogued in said data storing means are made up of words. | 0.906449 |
7,590,613 | 17 | 18 | 17. The information storage medium of claim 16 , wherein the template is further configured to define a set of ordering parameters for the analytic database function. | 17. The information storage medium of claim 16 , wherein the template is further configured to define a set of ordering parameters for the analytic database function. 18. The information storage medium of claim 17 , further comprising code for receiving one of the set of ordering parameters from the user. | 0.5 |
8,515,752 | 15 | 19 | 15. A non-transitory computer-readable medium to store instructions executable by one or more processors of one or more devices, the instructions comprising: one or more instructions to receive a voice search query; one or more instructions to determine recognition hypotheses based on the voice search query, where the recognition hypotheses are associated with a plurality of statistical weights that reflect respective likelihoods that the recognition hypotheses are accurate with respect to the voice search query; one or more instructions to select, based on the plurality of statistical weights and as selected recognition hypotheses, a plurality of the recognition hypotheses, where a quantity of the selected recognition hypotheses is based on a quantity of terms included in one of the selected recognition hypotheses and a maximum quantity of terms to be included in a weighted boolean query; one or more instructions to construct the weighted boolean query, where the weighted boolean query includes the selected recognition hypotheses, weighted by corresponding statistical weights of the plurality of statistical weights; and one or more instructions to obtain results associated with the weighted boolean query. | 15. A non-transitory computer-readable medium to store instructions executable by one or more processors of one or more devices, the instructions comprising: one or more instructions to receive a voice search query; one or more instructions to determine recognition hypotheses based on the voice search query, where the recognition hypotheses are associated with a plurality of statistical weights that reflect respective likelihoods that the recognition hypotheses are accurate with respect to the voice search query; one or more instructions to select, based on the plurality of statistical weights and as selected recognition hypotheses, a plurality of the recognition hypotheses, where a quantity of the selected recognition hypotheses is based on a quantity of terms included in one of the selected recognition hypotheses and a maximum quantity of terms to be included in a weighted boolean query; one or more instructions to construct the weighted boolean query, where the weighted boolean query includes the selected recognition hypotheses, weighted by corresponding statistical weights of the plurality of statistical weights; and one or more instructions to obtain results associated with the weighted boolean query. 19. The non-transitory computer-readable medium of claim 15 , where the one or more instructions to obtain the results include: one or more instructions to adjust a ranking of the results based on the corresponding statistical weights. | 0.78321 |
8,706,827 | 1 | 2 | 1. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, storing dialog patterns for a type of communication between a user and a type of recipient, the dialog patterns including at least one of words or phrases from one or more past communications between the user and one or more recipients of the type of recipient; generating a dialog profile for the type of recipient based at least in part upon the dialog patterns; determining at least one context associated with the user sending a communication to a recipient of the one or more recipients of the type of recipient, the at least one context being associated with at least one behavioral pattern of the user; determining a subsequent occurrence of the at least one context; adjusting the dialog profile associated with the recipient to include dialog patterns associated with the at least one context; generating at least one subsequent communication to be sent to the recipient based at least in part on the dialog patterns associated with the dialog profile of the recipient and the at least one context. | 1. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, storing dialog patterns for a type of communication between a user and a type of recipient, the dialog patterns including at least one of words or phrases from one or more past communications between the user and one or more recipients of the type of recipient; generating a dialog profile for the type of recipient based at least in part upon the dialog patterns; determining at least one context associated with the user sending a communication to a recipient of the one or more recipients of the type of recipient, the at least one context being associated with at least one behavioral pattern of the user; determining a subsequent occurrence of the at least one context; adjusting the dialog profile associated with the recipient to include dialog patterns associated with the at least one context; generating at least one subsequent communication to be sent to the recipient based at least in part on the dialog patterns associated with the dialog profile of the recipient and the at least one context. 2. The computer-implemented method of claim 1 , further comprising: enabling the user to approve the at least one subsequent communication before sending the at least one subsequent communication to the recipient. | 0.631488 |
7,913,159 | 16 | 24 | 16. A method comprising: displaying with a computing device an electronic form with first and second data-entry fields associated with first and second nodes in a hierarchical data file written in XML; enabling a user to input data into the first data-entry field through the computing device, the data being storable in the first node; receiving data input into the first data-entry field; validating the data, locally on the computing device, with a validation rule, in real time, and prior to enabling the user to input second data into the second data-entry field, to determine if the data is valid or invalid, wherein the validation rule is based on a part of a schema containing logic that governs the hierarchical data file, wherein the logic sets forth bounds of what data nodes the file can contain or the structure the nodes should have, and wherein the validation rule governs a node group of the hierarchical data file which includes the first node, and wherein validating is based on third data stored in a third node belonging to the node group, the third data having been entered into a third data-entry field mapped to the third node; and enabling the user to input the second data into the second data-entry field if the data input into the first data-entry field is valid, the second data being storable in the second node, or alerting the user if the data input into the first data-entry field is invalid. | 16. A method comprising: displaying with a computing device an electronic form with first and second data-entry fields associated with first and second nodes in a hierarchical data file written in XML; enabling a user to input data into the first data-entry field through the computing device, the data being storable in the first node; receiving data input into the first data-entry field; validating the data, locally on the computing device, with a validation rule, in real time, and prior to enabling the user to input second data into the second data-entry field, to determine if the data is valid or invalid, wherein the validation rule is based on a part of a schema containing logic that governs the hierarchical data file, wherein the logic sets forth bounds of what data nodes the file can contain or the structure the nodes should have, and wherein the validation rule governs a node group of the hierarchical data file which includes the first node, and wherein validating is based on third data stored in a third node belonging to the node group, the third data having been entered into a third data-entry field mapped to the third node; and enabling the user to input the second data into the second data-entry field if the data input into the first data-entry field is valid, the second data being storable in the second node, or alerting the user if the data input into the first data-entry field is invalid. 24. A method of claim 16 , wherein the validation rule written in a declarative syntax. | 0.72293 |
5,392,419 | 1 | 12 | 1. In a data processing system responsive to a plurality of input languages, each language adhering to a prescribed syntax, the presence of defined data portions ("For" keys) in incoming data indicating a vote for the presence of a language and the presence of other defined data portions ("Against" keys) indicating a vote Against the presence of the language, a method for identifying an input language comprising the steps of: a) analyzing, for each expected language, a syntax of an incoming block of data to identify For and Against keys in said block of data; b) providing For and Against tallies for each expected language in response to said analysis, each said tally being a summation of key entries, each key entry comprising an identified key count multiplied by a skew, the value of said skew indicating an importance of said key in said syntax and in the context of said block of data, said For tally summing entries of For keys and said Against tally summing entries of Against keys; c) comparing said For and Against tallies to determine whether or not they are so close as to signal uncertainty and, based upon a further syntactical characteristic of said block of data, resolving said uncertainty and indicating a value based on one of said tallies, said indication dependent upon whether said further syntactical characteristic indicates For or Against the language; d) indicating a value derived from the larger of the tallies in the event of no uncertainty between the tallies; and e) deciding, based upon said indicated value for each said expected language, the identity of a received language. | 1. In a data processing system responsive to a plurality of input languages, each language adhering to a prescribed syntax, the presence of defined data portions ("For" keys) in incoming data indicating a vote for the presence of a language and the presence of other defined data portions ("Against" keys) indicating a vote Against the presence of the language, a method for identifying an input language comprising the steps of: a) analyzing, for each expected language, a syntax of an incoming block of data to identify For and Against keys in said block of data; b) providing For and Against tallies for each expected language in response to said analysis, each said tally being a summation of key entries, each key entry comprising an identified key count multiplied by a skew, the value of said skew indicating an importance of said key in said syntax and in the context of said block of data, said For tally summing entries of For keys and said Against tally summing entries of Against keys; c) comparing said For and Against tallies to determine whether or not they are so close as to signal uncertainty and, based upon a further syntactical characteristic of said block of data, resolving said uncertainty and indicating a value based on one of said tallies, said indication dependent upon whether said further syntactical characteristic indicates For or Against the language; d) indicating a value derived from the larger of the tallies in the event of no uncertainty between the tallies; and e) deciding, based upon said indicated value for each said expected language, the identity of a received language. 12. The method as recited in claim 1 wherein said comparing step (c) includes the further step of: mapping said For and Against tallies into a preset range of values, each said tally mapped into said preset range of values in accordance with said tally's relationship to a maximum value each said tally can achieve. | 0.664179 |
7,934,161 | 14 | 20 | 14. An electronic system comprising: at least one processor; and at least one computer-readable storage medium encoded with executable instructions that, when executed by the at least one processor, causes the at least one processor to perform operations comprising: causing display of at least a portion of an interface that includes an input field configured to enable a user to enter input to define a search query; receiving first search input entered in the input field included in the interface; after receiving the first search input entered in the input field included in the interface: accessing a first search query based on the first search input entered in the input field included in the interface; initiating performance of a first search to identify search results that are responsive to the first search query; based on the first search to identify search results that are responsive to the first search query, accessing a first list of search results that are responsive to the first search query, the first list of search results including at least a first search result that is responsive to the first search query and that links to first electronic content; and causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, the display of the first list of search results having a representation of the first search result that includes description information that is descriptive of the first search result and a first link that links to the first electronic content; after user input selecting the first search result included in the display of the first list of search results, including the first search result in a second list of search results that is different from the first list of search results and that, when displayed, includes a reformatted representation of the first search result that has reduced description information of the first search result as compared to the description information included in the representation of the first search result in the display of the first list of search results; after including the first search result in the second list of search results, receiving second search input, the second search input being different than the first search input; after receiving the second search input: accessing a second search query based on the second search input, the second search query being different than the first search query, initiating performance of a second search to identify search results that are responsive to the second search query, and accessing search results based on the second search to identify search results that are responsive to the second search query that is different than the first search query; after accessing search results based on the second search to identify search results that are responsive to the second search query that is different than the first search query and that was accessed after including the first search result in the second list of search results, including, in the second list of search results, a second search result identified in the second search such that the second list of search results includes the first search result which is responsive to the first search query and the second search result which is responsive to the second search query; after including the first search result in the second list of search results and including the second search result in the second list of search results, receiving third search input, the third search input being different than the first search input and the second search input; after receiving the third search input: accessing a third search query based on the third search input, the third search query being different than the first search query and the second search query, initiating performance of a third search to identify search results that are responsive to the third search query, and accessing search results based on the third search to identify search results that are responsive to the third search query that is different than the first search query and the second search query; after accessing search results based on the third search to identify search results that are responsive to the third search query that is different than the first search query and the second search query and that was accessed after including the first search result and the second search result in the second list of search results, including, in the second list of search results, a third search result identified in the third search such that the second list of search results includes the first search result which is responsive to the first search query, the second search result which is responsive to the second search query, and the third search result which is responsive to the third search query. | 14. An electronic system comprising: at least one processor; and at least one computer-readable storage medium encoded with executable instructions that, when executed by the at least one processor, causes the at least one processor to perform operations comprising: causing display of at least a portion of an interface that includes an input field configured to enable a user to enter input to define a search query; receiving first search input entered in the input field included in the interface; after receiving the first search input entered in the input field included in the interface: accessing a first search query based on the first search input entered in the input field included in the interface; initiating performance of a first search to identify search results that are responsive to the first search query; based on the first search to identify search results that are responsive to the first search query, accessing a first list of search results that are responsive to the first search query, the first list of search results including at least a first search result that is responsive to the first search query and that links to first electronic content; and causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, the display of the first list of search results having a representation of the first search result that includes description information that is descriptive of the first search result and a first link that links to the first electronic content; after user input selecting the first search result included in the display of the first list of search results, including the first search result in a second list of search results that is different from the first list of search results and that, when displayed, includes a reformatted representation of the first search result that has reduced description information of the first search result as compared to the description information included in the representation of the first search result in the display of the first list of search results; after including the first search result in the second list of search results, receiving second search input, the second search input being different than the first search input; after receiving the second search input: accessing a second search query based on the second search input, the second search query being different than the first search query, initiating performance of a second search to identify search results that are responsive to the second search query, and accessing search results based on the second search to identify search results that are responsive to the second search query that is different than the first search query; after accessing search results based on the second search to identify search results that are responsive to the second search query that is different than the first search query and that was accessed after including the first search result in the second list of search results, including, in the second list of search results, a second search result identified in the second search such that the second list of search results includes the first search result which is responsive to the first search query and the second search result which is responsive to the second search query; after including the first search result in the second list of search results and including the second search result in the second list of search results, receiving third search input, the third search input being different than the first search input and the second search input; after receiving the third search input: accessing a third search query based on the third search input, the third search query being different than the first search query and the second search query, initiating performance of a third search to identify search results that are responsive to the third search query, and accessing search results based on the third search to identify search results that are responsive to the third search query that is different than the first search query and the second search query; after accessing search results based on the third search to identify search results that are responsive to the third search query that is different than the first search query and the second search query and that was accessed after including the first search result and the second search result in the second list of search results, including, in the second list of search results, a third search result identified in the third search such that the second list of search results includes the first search result which is responsive to the first search query, the second search result which is responsive to the second search query, and the third search result which is responsive to the third search query. 20. The electronic system of claim 14 : wherein including, in the second list of search results, a second search result identified in the second search comprises including the second search result at an end of the second list of search results immediately following the first search result; and wherein including, in the second list of search results, a third search result identified in the third search comprises including the third search result at an end of the second list of search results immediately following the second search result. | 0.650579 |
10,032,214 | 3 | 4 | 3. The method of claim 2 , wherein the analyzing further comprises: organizing the name-value pairs according to value sets based on definition information; and clustering the value sets based on the definition information to generate a plurality of groups. | 3. The method of claim 2 , wherein the analyzing further comprises: organizing the name-value pairs according to value sets based on definition information; and clustering the value sets based on the definition information to generate a plurality of groups. 4. The method of claim 3 , wherein the analyzing further comprises: validating the plurality of groups based on catalogue information to identify whether the plurality of groups includes a first group that corresponds to the first application. | 0.5 |
9,002,111 | 1 | 3 | 1. A system, comprising: a computer processor; and logic executable by the computer processor, the logic configured to implement a method, the method including: determining an image as a candidate for a scaling process; scanning the image and identifying text in the image from the scanning; scaling the image to a next lower resolution, the scaling comprising reducing a set of pixel dimensions to a nearest lower rendering level; iteratively performing the scaling process until a threshold value of a readability metric is reached, the scaling process including: scanning the scaled image for scaled text; comparing a difference between the text and the scaled text to the difference indicative of the readability metric; and scaling the scaled image to a next lower resolution; and responsive to reaching the threshold value of the readability metric, selecting from scaled images an image having a lowest resolution resulting from the scaling process before the threshold value of the readability metric was reached; wherein the readability metric is calculated as a function of a Levenshtein Distance between the text and the scaled text, and a length of the original text. | 1. A system, comprising: a computer processor; and logic executable by the computer processor, the logic configured to implement a method, the method including: determining an image as a candidate for a scaling process; scanning the image and identifying text in the image from the scanning; scaling the image to a next lower resolution, the scaling comprising reducing a set of pixel dimensions to a nearest lower rendering level; iteratively performing the scaling process until a threshold value of a readability metric is reached, the scaling process including: scanning the scaled image for scaled text; comparing a difference between the text and the scaled text to the difference indicative of the readability metric; and scaling the scaled image to a next lower resolution; and responsive to reaching the threshold value of the readability metric, selecting from scaled images an image having a lowest resolution resulting from the scaling process before the threshold value of the readability metric was reached; wherein the readability metric is calculated as a function of a Levenshtein Distance between the text and the scaled text, and a length of the original text. 3. The system of claim 1 , wherein the identifying text is implemented using optical character recognition. | 0.709239 |
8,407,233 | 1 | 12 | 1. A method, using a processor, of calculating relevance among words based on a relevance of each word in a document, the method comprising: generating statistical information associated with relevance among words by calculating a crossing frequency of words associated with a number of times of each of cross-word being appeared in a document, an appearance frequency of a word, or a word-word combination frequency associated with an appearance and a non-appearance of a combination of a first word and a second word, wherein the appearance frequency is a number of times that a word appears and frequency information is generated based on one of the appearance frequency or the crossing frequency, or the word-word combination frequency to provide the statistical information, the calculation being performed by the processor according to word-word or word-document classification; standardizing the statistical information by applying a parameter to the calculated statistical information, wherein the standardizing the statistical information comprises generating a combination probability distribution of a random variable corresponding to a pair of words and standardizing the statistical information based on the word-word combination frequency, wherein the word-word combination frequency associated with the pair of words is a number of documents that include all words in the pair, a number of documents that do not include any word in the pair, and a number of documents that include one of the words in the pair, and wherein the random variable is defined in a point space of columns and rows that comprise appearance or non-appearance points of the word; determining, by the processor, the relevance among the words as a numerical value based on the standardization; and providing the numerical value associated with the relevance among words to a search system. | 1. A method, using a processor, of calculating relevance among words based on a relevance of each word in a document, the method comprising: generating statistical information associated with relevance among words by calculating a crossing frequency of words associated with a number of times of each of cross-word being appeared in a document, an appearance frequency of a word, or a word-word combination frequency associated with an appearance and a non-appearance of a combination of a first word and a second word, wherein the appearance frequency is a number of times that a word appears and frequency information is generated based on one of the appearance frequency or the crossing frequency, or the word-word combination frequency to provide the statistical information, the calculation being performed by the processor according to word-word or word-document classification; standardizing the statistical information by applying a parameter to the calculated statistical information, wherein the standardizing the statistical information comprises generating a combination probability distribution of a random variable corresponding to a pair of words and standardizing the statistical information based on the word-word combination frequency, wherein the word-word combination frequency associated with the pair of words is a number of documents that include all words in the pair, a number of documents that do not include any word in the pair, and a number of documents that include one of the words in the pair, and wherein the random variable is defined in a point space of columns and rows that comprise appearance or non-appearance points of the word; determining, by the processor, the relevance among the words as a numerical value based on the standardization; and providing the numerical value associated with the relevance among words to a search system. 12. The method of claim 1 , wherein the calculation comprises calculating the relevance between the words based on information about two random variables of a combination probability distribution that is determined based on the generated statistical information. | 0.776451 |
10,083,169 | 1 | 2 | 1. A method comprising: receiving a first sequence of words arranged according to a first order, wherein the first sequence of words comprises a plurality of sentences of words, the plurality of sentences being in an input order; for each word in the first sequence of words, beginning with a first word in the first order: determining a topic vector that is associated with the word, generating a combined input from the word and the topic vector, and processing the combined input through one or more sequence modeling layers to generate a respective sequence modeling output for the word; and processing one or more of the respective sequence modeling outputs through an output layer to generate a neural network output for the first sequence of words, wherein, for each word in each sentence after a first sentence in the input order, determining the topic vector that is associated with the word is based, at least in part, on a sequence modeling output for a last word in a sentence immediately before the sentence in the input order. | 1. A method comprising: receiving a first sequence of words arranged according to a first order, wherein the first sequence of words comprises a plurality of sentences of words, the plurality of sentences being in an input order; for each word in the first sequence of words, beginning with a first word in the first order: determining a topic vector that is associated with the word, generating a combined input from the word and the topic vector, and processing the combined input through one or more sequence modeling layers to generate a respective sequence modeling output for the word; and processing one or more of the respective sequence modeling outputs through an output layer to generate a neural network output for the first sequence of words, wherein, for each word in each sentence after a first sentence in the input order, determining the topic vector that is associated with the word is based, at least in part, on a sequence modeling output for a last word in a sentence immediately before the sentence in the input order. 2. The method of claim 1 , wherein the one or more sequence modeling layers are recurrent neural network layers. | 0.945313 |
6,163,775 | 31 | 37 | 31. A method for storing and retrieving data in a computer system having a memory, a central processing unit and a display, comprising the steps of: configuring said memory according to a logical table, said logical table including: a plurality of cells, each said cell having a first address segment and a second address segment; a plurality of attribute sets, each said attribute set including a series of cells having the same second address segment, each said attribute set including an object identification number (OID) to identify each said attribute set; and a plurality of records, each said record including a series of cells having the same first address segment, each said record including an OID to identify each said record, wherein at least one of said records has an OID equal to the OID of a corresponding one of said attribute sets, and at least one of said records includes attribute set information defining each of said attribute sets. | 31. A method for storing and retrieving data in a computer system having a memory, a central processing unit and a display, comprising the steps of: configuring said memory according to a logical table, said logical table including: a plurality of cells, each said cell having a first address segment and a second address segment; a plurality of attribute sets, each said attribute set including a series of cells having the same second address segment, each said attribute set including an object identification number (OID) to identify each said attribute set; and a plurality of records, each said record including a series of cells having the same first address segment, each said record including an OID to identify each said record, wherein at least one of said records has an OID equal to the OID of a corresponding one of said attribute sets, and at least one of said records includes attribute set information defining each of said attribute sets. 37. The method of claim 31 wherein at least one of said attribute sets defines cells that include a plurality of pointers to other attribute sets within the same record, said pointers indicating those attribute sets within the same record that contain defined values. | 0.514545 |
8,214,346 | 32 | 35 | 32. The computer program product of claim 26 , wherein determining the at least one term vector includes building a list and a count of taxonomic nouns. | 32. The computer program product of claim 26 , wherein determining the at least one term vector includes building a list and a count of taxonomic nouns. 35. The computer program product of claim 32 , wherein determining the at least one term vector includes applying a dictionary of taxonomic nouns with a dictionary building server. | 0.5 |
8,041,741 | 1 | 3 | 1. A computer-implemented method for collecting information about a group of documents, comprising: under control of one or more computer systems configured with executable instructions, seeding the group of documents with one or more seed documents; identifying, in at least a portion of the group of documents, at least one reference to at least one secondary document; adding to the group of documents at least one secondary document obtainable using the identified at least one reference; identifying, for at least a portion of the documents in the group of documents, two or more attribute values associated with at least one aspect of the document; adding at least a portion of the identified attribute values to a set of information associated with the group of documents, the set of information enabling documents in the group of documents to be located based at least in part upon any of the attribute values in the set of information; applying a test to at least one secondary document; and adding the attribute values identified for the at least one secondary document to the set of information associated with the group of documents only if the applied test is satisfied. | 1. A computer-implemented method for collecting information about a group of documents, comprising: under control of one or more computer systems configured with executable instructions, seeding the group of documents with one or more seed documents; identifying, in at least a portion of the group of documents, at least one reference to at least one secondary document; adding to the group of documents at least one secondary document obtainable using the identified at least one reference; identifying, for at least a portion of the documents in the group of documents, two or more attribute values associated with at least one aspect of the document; adding at least a portion of the identified attribute values to a set of information associated with the group of documents, the set of information enabling documents in the group of documents to be located based at least in part upon any of the attribute values in the set of information; applying a test to at least one secondary document; and adding the attribute values identified for the at least one secondary document to the set of information associated with the group of documents only if the applied test is satisfied. 3. The computer-implemented method of claim 1 , wherein at least a portion of the secondary documents added to the group of documents comprise web pages. | 0.773669 |
9,332,401 | 19 | 20 | 19. The computer program product of claim 15 , wherein converting content further comprises: computer usable program code configured to capture text provided as input for the announcement in a digital format. | 19. The computer program product of claim 15 , wherein converting content further comprises: computer usable program code configured to capture text provided as input for the announcement in a digital format. 20. The computer program product of claim 19 , wherein, when the content is to be provided in an audio format, said translating of the content further comprises: computer usable program code configured to transform the text of the translated content into audio using a text-to-speech engine appropriate to the corresponding native language. | 0.5 |
8,019,714 | 1 | 2 | 1. A method for operating a human-made thinking system including one or more CPU's, one or more I/O devices, and one or more memories, comprising the steps of : (a) establishing in said one or more memories a knowledge structure comprising a file organizing mechanism, and more than one element file wherein each element file individually and separately includes identifying information and knowledge information corresponding to only one element; wherein the identifying information categorizes and identifies the corresponding element, wherein the knowledge information includes knowledge about the corresponding element, wherein the knowledge is information related to at least one direct link of each element with one or more elements of the knowledge structure thus connects element to at least one other element; (b) establishing a process structure comprising at least one process file; (c) establishing an execution system comprising an internal control mechanism, and at least one thinking mode; wherein the internal control mechanism includes at least one internal control rule, and at least one structure rule, wherein the thinking mode includes at least one corresponding thinking rule; (d) running the executing system wherein the internal control mechanism can operate without human intervention wherein the thinking mode can be activated according o the internal control rules of internal control mechanism; wherein according to the thinking rule, a direct link between a first existing element and a second existing element can be used to establish one or more new direct links between said first existing element and at least one other existing element that has an existing direct link with said second existing element; wherein according to the thinking rule, process files can be used to establish new direct links between the existing elements, and store or output said new direct links as desired. | 1. A method for operating a human-made thinking system including one or more CPU's, one or more I/O devices, and one or more memories, comprising the steps of : (a) establishing in said one or more memories a knowledge structure comprising a file organizing mechanism, and more than one element file wherein each element file individually and separately includes identifying information and knowledge information corresponding to only one element; wherein the identifying information categorizes and identifies the corresponding element, wherein the knowledge information includes knowledge about the corresponding element, wherein the knowledge is information related to at least one direct link of each element with one or more elements of the knowledge structure thus connects element to at least one other element; (b) establishing a process structure comprising at least one process file; (c) establishing an execution system comprising an internal control mechanism, and at least one thinking mode; wherein the internal control mechanism includes at least one internal control rule, and at least one structure rule, wherein the thinking mode includes at least one corresponding thinking rule; (d) running the executing system wherein the internal control mechanism can operate without human intervention wherein the thinking mode can be activated according o the internal control rules of internal control mechanism; wherein according to the thinking rule, a direct link between a first existing element and a second existing element can be used to establish one or more new direct links between said first existing element and at least one other existing element that has an existing direct link with said second existing element; wherein according to the thinking rule, process files can be used to establish new direct links between the existing elements, and store or output said new direct links as desired. 2. The method as claimed in claim 1 , wherein the executing system further comprises an inputting mode, a reading mode, a writing mode, a memorizing mode, an outputting mode, an inquiry mode, verification mode, and a system update mode; wherein the inputting mode includes at least one inputting rule, wherein the reading mode includes at least one reading rule, wherein the writing mode includes at least one writing rule, wherein the memorizing mode includes at least one memorizing rule, wherein the outputting mode includes at least one outputting rule, wherein the inquiry mode includes at least one inquiring rule, wherein the verification mode includes at least one verification rule, wherein the system update mode includes system update rules; wherein the internal control mechanism will operate the inputting mode, the reading mode, the thinking mode, the writing mode, the memorizing mode, the outputting mode, the inquiry mode, the verification mode according to the internal control rules of internal control mechanism. | 0.5 |
5,590,319 | 12 | 13 | 12. A method in accordance with claim 11, further comprising normalizing said input query signals by removing references to views. | 12. A method in accordance with claim 11, further comprising normalizing said input query signals by removing references to views. 13. A method in accordance with claim 12, further comprising converting said signals indicative of trees representing said output queries to signals indicative of text. | 0.5 |
9,794,405 | 1 | 15 | 1. A method comprising: detecting, by a system including a processor, an input incompatible with an original script for an interactive communication over a communication network, wherein the detecting is performed during the interactive communication; generating, by the system and during the interactive communication, a dynamically updated script different from the original script in accordance with a type of the incompatible input; and providing, by the system and over the communication network, information to a device participating in the interactive communication in accordance with the dynamically updated script, wherein at least a portion of a remainder of the interactive communication is conducted in accordance with the dynamically updated script. | 1. A method comprising: detecting, by a system including a processor, an input incompatible with an original script for an interactive communication over a communication network, wherein the detecting is performed during the interactive communication; generating, by the system and during the interactive communication, a dynamically updated script different from the original script in accordance with a type of the incompatible input; and providing, by the system and over the communication network, information to a device participating in the interactive communication in accordance with the dynamically updated script, wherein at least a portion of a remainder of the interactive communication is conducted in accordance with the dynamically updated script. 15. The method of claim 1 , wherein the generating the dynamically updated script comprises switching an accepted form of input for the remainder of the interaction communication. | 0.637652 |
5,421,731 | 1 | 7 | 1. A method for teaching reading to a learner comprising: (a) showing to the learner a printed word to be read, the printed word having at least two syllables; (b) directing the learner to decode the printed word, by having the learner (i) identify all vowels in the printed word, (ii) identify all consonants in the primed word beginning with the first consonant after the first vowel and ending with the consonant before the last vowel, (iii) identify all syllables in the primed word using syllabication rules previously taught to the learner, (iv) identify all phonograms in the printed word, where each phonogram in a syllable is from the first vowel to the end of the syllable, and identify any consonant or consonant clusters preceding the phonogram in each syllable with the exception of suffixes, and (v) identify each suffix, if any; (c) directing the learner, after the learner has decoded the printed word, to pronounce the printed word using the decoded syllables, phonograms, consonants, consonant clusters, and suffixes; and, (d) having the learner listen to correct pronunciation of the printed word. | 1. A method for teaching reading to a learner comprising: (a) showing to the learner a printed word to be read, the printed word having at least two syllables; (b) directing the learner to decode the printed word, by having the learner (i) identify all vowels in the printed word, (ii) identify all consonants in the primed word beginning with the first consonant after the first vowel and ending with the consonant before the last vowel, (iii) identify all syllables in the primed word using syllabication rules previously taught to the learner, (iv) identify all phonograms in the printed word, where each phonogram in a syllable is from the first vowel to the end of the syllable, and identify any consonant or consonant clusters preceding the phonogram in each syllable with the exception of suffixes, and (v) identify each suffix, if any; (c) directing the learner, after the learner has decoded the printed word, to pronounce the printed word using the decoded syllables, phonograms, consonants, consonant clusters, and suffixes; and, (d) having the learner listen to correct pronunciation of the printed word. 7. The method of claim 1 wherein said syllabication rules for three syllable words include syllabifying a vowel(V)-consonant(C)-vowel(V)-consonant(C)-vowel (V) pattern into the syllables VC, V and CV when the last vowel of the printed word is not a last "e." | 0.878645 |
9,582,494 | 9 | 11 | 9. An executable software product stored on a non-transitory computer-readable storage medium containing program instructions for automatically extracting objects from a presentation-oriented document, the program instructions for: receiving as input by a computer the presentation-oriented document (POD) and a set of descriptors, the POD comprising content elements are spatially arranged in a given layout organization for presenting contents to human users, wherein the computer is configured to process PODs having different formats, including webpage formats and Portable Document Format (PDF) formats, and wherein the set of descriptors that define the objects to extract from the POD by defining both spatial relationships between objects in the POD as well as semantics of the objects expressed as zero more attributes comprising the objects; using the set of descriptors to identify content elements in the POD that match the attributes in the set of descriptors defining the objects, and assigning semantic annotations to the identified content elements based on the descriptors; creating a semantic and spatial document model (SSDM) containing one or more of spatial structures of the identified content elements, presentation/visual features of the identified content elements, and the semantic annotations assigned to the identified contents elements; extracting the identified content elements from the POD based on the set of descriptors and the SSDM to create a set of object instances; performing at least one of: i) using the object instances to generate semantic and spatial wrappers that can be reused on a different POD, and ii) storing the object instances in a data repository. | 9. An executable software product stored on a non-transitory computer-readable storage medium containing program instructions for automatically extracting objects from a presentation-oriented document, the program instructions for: receiving as input by a computer the presentation-oriented document (POD) and a set of descriptors, the POD comprising content elements are spatially arranged in a given layout organization for presenting contents to human users, wherein the computer is configured to process PODs having different formats, including webpage formats and Portable Document Format (PDF) formats, and wherein the set of descriptors that define the objects to extract from the POD by defining both spatial relationships between objects in the POD as well as semantics of the objects expressed as zero more attributes comprising the objects; using the set of descriptors to identify content elements in the POD that match the attributes in the set of descriptors defining the objects, and assigning semantic annotations to the identified content elements based on the descriptors; creating a semantic and spatial document model (SSDM) containing one or more of spatial structures of the identified content elements, presentation/visual features of the identified content elements, and the semantic annotations assigned to the identified contents elements; extracting the identified content elements from the POD based on the set of descriptors and the SSDM to create a set of object instances; performing at least one of: i) using the object instances to generate semantic and spatial wrappers that can be reused on a different POD, and ii) storing the object instances in a data repository. 11. The executable software product of claim 9 , wherein receiving the set of descriptors further comprises program instructions for: compiling the set of descriptors into a set of compiled annotation descriptors and compiled object descriptors. | 0.803371 |
5,440,495 | 2 | 3 | 2. A control device for evaluating a reed in a jet loom, comprising: information generating means for detecting a last released timing and a last arrival timing of a weft to be inserted and generating the timing informations corresponding thereto; and judging means for evaluating a reed by obtaining, on the basis of both said timing informations outputted from said information generating means, the extent of dispersion of the last released timing and the extent of dispersion of the last arrival timing, and then evaluating the reed on the basis of both said obtained extents. | 2. A control device for evaluating a reed in a jet loom, comprising: information generating means for detecting a last released timing and a last arrival timing of a weft to be inserted and generating the timing informations corresponding thereto; and judging means for evaluating a reed by obtaining, on the basis of both said timing informations outputted from said information generating means, the extent of dispersion of the last released timing and the extent of dispersion of the last arrival timing, and then evaluating the reed on the basis of both said obtained extents. 3. A control device according to claim 2, wherein said judging means evaluate said reed on the basis of both said obtained extents and the subpressure for weft inserting. | 0.5 |
9,953,652 | 6 | 9 | 6. The computer-implemented method of claim 5 , wherein the identifying the first subset comprises using a statistical model, and wherein the statistical model comprises a conditional random field model, a hidden Markov model, a maximum entropy Markov model, a structure prediction model, or a sequential model. | 6. The computer-implemented method of claim 5 , wherein the identifying the first subset comprises using a statistical model, and wherein the statistical model comprises a conditional random field model, a hidden Markov model, a maximum entropy Markov model, a structure prediction model, or a sequential model. 9. The computer-implemented method of claim 6 , further comprising generating the statistical model using weakly supervised training data, wherein the weakly supervised training data is based at least partly on an automated analysis of previously submitted search queries to identify entities in the previously submitted search queries. | 0.5 |
9,507,947 | 1 | 11 | 1. A method of performing data loss prevention on content from a content source, the method comprising: generating, by processing circuitry, multiple variants from the content, the multiple variants including a set of variants for each parsed word of the content, each variant of the set (i) including multiple characters and (ii) differing from other variants of the set by at least one character; performing, by the processing circuitry, evaluation operations to determine whether any of the variants includes sensitive data; and in response to the evaluation operations, performing, by the processing circuitry, a control operation which (i) releases all of the parsed words of the content to a destination when none of the variants is determined to include sensitive data, and (ii) blocks at least one parsed word of the content from reaching the destination when at least one variant is determined to include sensitive data; wherein generating the multiple variants from the content includes: applying a set of predefined transformations from a transformation database to the content from the content source to form the multiple variants. | 1. A method of performing data loss prevention on content from a content source, the method comprising: generating, by processing circuitry, multiple variants from the content, the multiple variants including a set of variants for each parsed word of the content, each variant of the set (i) including multiple characters and (ii) differing from other variants of the set by at least one character; performing, by the processing circuitry, evaluation operations to determine whether any of the variants includes sensitive data; and in response to the evaluation operations, performing, by the processing circuitry, a control operation which (i) releases all of the parsed words of the content to a destination when none of the variants is determined to include sensitive data, and (ii) blocks at least one parsed word of the content from reaching the destination when at least one variant is determined to include sensitive data; wherein generating the multiple variants from the content includes: applying a set of predefined transformations from a transformation database to the content from the content source to form the multiple variants. 11. A method as in claim 1 wherein the content source is an image scan; and wherein generating multiple variants from the content further includes: during a content extraction phase in which the image scan is recognized using optical character recognition (OCR), generating (i) first word variants for a first parsed word of the image scan and (ii) second word variants for a second parsed word of the image scan. | 0.608902 |
9,946,510 | 1 | 4 | 1. A mobile terminal, comprising: a detachable stylus pen including a microphone and a memory; a touch screen configured to output an execution screen of an application; a wireless communication unit configured to receive a voice signal from the stylus pen, the voice signal generated in response to at least one voice received via the microphone while text is input onto the execution screen according to movement of the stylus pen that is detached from the mobile terminal, and the generated voice signal stored in the memory of the stylus pen such that the received at least one voice is stored as a recorded voice memo; and a controller configured to: execute the application; cause the touch screen to display text corresponding to at least a portion of the received voice signal at a specific position of the execution screen in response to selection of the specific position by the detached stylus pen; cause the touch screen to display a pop-up window including a list of a plurality of texts, each text in the list corresponding to a respective one of a plurality of voice data included in the at least one voice and one of the plurality of texts displayed distinctively over the rest of the plurality of texts in the list, such that one of the plurality of texts is selected from the list; and cause the touch screen to display a recording indicator indicating that the voice memo is being recorded, the recording indicator displayed while the text is input onto the execution screen, wherein the distinctively displayed one of the plurality of texts in the list is recommended based on the specific position for its closest relationship with the specific position among the plurality of texts in the list. | 1. A mobile terminal, comprising: a detachable stylus pen including a microphone and a memory; a touch screen configured to output an execution screen of an application; a wireless communication unit configured to receive a voice signal from the stylus pen, the voice signal generated in response to at least one voice received via the microphone while text is input onto the execution screen according to movement of the stylus pen that is detached from the mobile terminal, and the generated voice signal stored in the memory of the stylus pen such that the received at least one voice is stored as a recorded voice memo; and a controller configured to: execute the application; cause the touch screen to display text corresponding to at least a portion of the received voice signal at a specific position of the execution screen in response to selection of the specific position by the detached stylus pen; cause the touch screen to display a pop-up window including a list of a plurality of texts, each text in the list corresponding to a respective one of a plurality of voice data included in the at least one voice and one of the plurality of texts displayed distinctively over the rest of the plurality of texts in the list, such that one of the plurality of texts is selected from the list; and cause the touch screen to display a recording indicator indicating that the voice memo is being recorded, the recording indicator displayed while the text is input onto the execution screen, wherein the distinctively displayed one of the plurality of texts in the list is recommended based on the specific position for its closest relationship with the specific position among the plurality of texts in the list. 4. The mobile terminal of claim 1 , wherein the controller is further configured to cause the touch screen to output a list of candidate words for replacing a word of the displayed text in response to selection of the word. | 0.759179 |
9,047,873 | 1 | 9 | 1. A communication apparatus comprising: a microphone to receive sound when a user speaks and to convert the received sound into a voice signal; a voice activity detection processor to detect spoken words and informative sounds within the voice signal; a voice-to-text processor programmed to convert the spoken words and the informative sounds of the voice signal into a text message, wherein the text message includes text identifying the user as originator of the voice signal; a transmitter configured to transmit the voice signal, the text message, or both the voice signal and text message to other users; a receiver configured to receive one or more voice signals, text messages, or voice signals and text messages from one or more users via a communication network; a protective facemask; and a display device to display, adjacent or integral to the protective facemask, the one or more text messages from the one or more users. | 1. A communication apparatus comprising: a microphone to receive sound when a user speaks and to convert the received sound into a voice signal; a voice activity detection processor to detect spoken words and informative sounds within the voice signal; a voice-to-text processor programmed to convert the spoken words and the informative sounds of the voice signal into a text message, wherein the text message includes text identifying the user as originator of the voice signal; a transmitter configured to transmit the voice signal, the text message, or both the voice signal and text message to other users; a receiver configured to receive one or more voice signals, text messages, or voice signals and text messages from one or more users via a communication network; a protective facemask; and a display device to display, adjacent or integral to the protective facemask, the one or more text messages from the one or more users. 9. The communication apparatus of claim 1 , wherein the display device is a transparent organic light emitting diode (OLED) device embedded in a facemask of the user. | 0.897909 |
9,620,117 | 1 | 2 | 1. A method comprising: obtaining, during an unsupervised classification phase of a spoken dialog system, a semantic classifier input and a corresponding label attributed to the semantic classifier input; determining, via a processor, whether the corresponding label is correct based on logged interaction data, to yield a correctness result, wherein the logged interaction data comprises: data describing user speech; a non-speech user action indicating one of a negative training example and a positive training example; and an input/output pair having an input and an output, the input comprising a speech recognition result in a lattice form and the output comprising one of an outcome of a call, a confirmation by a user, and a call hang-up, the output being a result of the input; generating an entry for an adaptation corpus based on the correctness result; and adapting operation of a semantic classifier based on the adaptation corpus. | 1. A method comprising: obtaining, during an unsupervised classification phase of a spoken dialog system, a semantic classifier input and a corresponding label attributed to the semantic classifier input; determining, via a processor, whether the corresponding label is correct based on logged interaction data, to yield a correctness result, wherein the logged interaction data comprises: data describing user speech; a non-speech user action indicating one of a negative training example and a positive training example; and an input/output pair having an input and an output, the input comprising a speech recognition result in a lattice form and the output comprising one of an outcome of a call, a confirmation by a user, and a call hang-up, the output being a result of the input; generating an entry for an adaptation corpus based on the correctness result; and adapting operation of a semantic classifier based on the adaptation corpus. 2. The method of claim 1 , wherein determining whether the corresponding label is correct indicates whether the label attributed by the semantic classifier is one of a correct label and an incorrect label. | 0.751214 |
4,553,657 | 8 | 9 | 8. In the token system of claim 7, said slide being operative between a first position wherein said first magnetic means is positioned at said upper station and said second magnetic means is positioned at said lower station and a second position wherein neither of said first or second magnetic means is in communication with either of said upper or lower stations, said counterfeit and valid tokens being removed from said upper and lower stations, respectively, and being guided to said first and second outlet slots, respectively, upon movement of said slide to said second position thereof. | 8. In the token system of claim 7, said slide being operative between a first position wherein said first magnetic means is positioned at said upper station and said second magnetic means is positioned at said lower station and a second position wherein neither of said first or second magnetic means is in communication with either of said upper or lower stations, said counterfeit and valid tokens being removed from said upper and lower stations, respectively, and being guided to said first and second outlet slots, respectively, upon movement of said slide to said second position thereof. 9. In the token system of claim 8, said body having means formed therein adjacent said upper station for engaging said counterfeit token when said slide is moved from the first position thereof to the second position thereof to release said counterfeit token from said first magnetic means, said inlet slot communicating with said first outlet slot when said slide is in said second position thereof so that when said counterfeit token is released from said first magnetic means, it drops into said first outlet slot and is released from said body. | 0.5 |
8,751,239 | 15 | 19 | 15. An apparatus comprising a processor and memory storing computer program code, the memory and computer program code configured to, with the processor cause the apparatus at least to: train, at a user terminal, a first voice conversion model with respect to a training source speech of a first speaker and a second voice conversion model with respect to a training target speech of a second speaker; wherein training the first voice conversion model further comprises determining a first conversion function for transforming any source speech into corresponding synthetic speech, the first conversion function receiving the training source speech of the first speaker and a training source synthetic speech of the first speaker as inputs, and wherein training the second voice conversion model further comprises determining a second conversion function for transforming synthetic speech into corresponding target speech, the second conversion function receiving the training target speech of the second speaker and a training target synthetic speech of the second speaker as inputs, and wherein said training target synthetic speech is produced from said training target speech; process, at the user terminal, source speech of the first speaker using the first voice conversion model to convert the source speech to synthetic speech; and process, at the user terminal, an output of the first voice conversion model at the second voice conversion model to produce target speech corresponding to the source speech. | 15. An apparatus comprising a processor and memory storing computer program code, the memory and computer program code configured to, with the processor cause the apparatus at least to: train, at a user terminal, a first voice conversion model with respect to a training source speech of a first speaker and a second voice conversion model with respect to a training target speech of a second speaker; wherein training the first voice conversion model further comprises determining a first conversion function for transforming any source speech into corresponding synthetic speech, the first conversion function receiving the training source speech of the first speaker and a training source synthetic speech of the first speaker as inputs, and wherein training the second voice conversion model further comprises determining a second conversion function for transforming synthetic speech into corresponding target speech, the second conversion function receiving the training target speech of the second speaker and a training target synthetic speech of the second speaker as inputs, and wherein said training target synthetic speech is produced from said training target speech; process, at the user terminal, source speech of the first speaker using the first voice conversion model to convert the source speech to synthetic speech; and process, at the user terminal, an output of the first voice conversion model at the second voice conversion model to produce target speech corresponding to the source speech. 19. The apparatus of claim 15 , wherein the memory and the computer program code are further configured to, with the processor, cause the apparatus to convert the source speech to intermediate synthetic speech based on the first voice conversion model. | 0.5 |
7,567,945 | 1 | 2 | 1. A computer-implemented method of determining the outcome of performing an aggregation-type operation on facts contained in a full structured collection of fact records, wherein the full structured collection of fact records is comprised of a plurality of component structured collections of fact records, the facts being data representative of interaction by users with information presented to the users via a computing network and each component structured collection of facts being for facts indicating user interaction during a particular time period the method comprising: by a computing system, sampling the plurality of component structured collections of fact records in a deterministic manner across the component structured collections of facts, wherein the sampling includes applying a sampling algorithm to values of a particular eminent attribute of the fact records consistently across the component structured collections of fact records, wherein the algorithm is characterized by deterministically distributing the fact records relative to the eminent attribute, the particular eminent attribute being a dimension of every one of the component structured collections of fact records, by the computing system, forming a merged collection of sampled fact records comprising the fact records sampled from the plurality of component structured collections of fact records, such that the merged collection of sampled fact records is longitudinal for records having the at least one particular eminent attribute value, over multiple time periods; by the computing system, performing an aggregation operation on the merged collection of sampled fact records to determine an aggregation result, the aggregation operates at a same level as the particular eminent attribute value and the aggregation result being an aggregate value representing an aggreate of the facts of the merged collection of sampled fact records; and by the computing system, based on the determined aggregation result and on an indication of characteristics of facts of the sampled fact records relative to the facts of the full structured collection of fact records, determining an indication of a statistical measure of a difference between what would be the result of the aggregation-type operation on the facts of the full structured collection of fact records and the actual result of the aggregation-type operation on facts of the sampled fact records, wherein the indication of the statistical measure of the difference indicates a confidence associated with the result of the aggregation-type operation on the sampled subset of facts. | 1. A computer-implemented method of determining the outcome of performing an aggregation-type operation on facts contained in a full structured collection of fact records, wherein the full structured collection of fact records is comprised of a plurality of component structured collections of fact records, the facts being data representative of interaction by users with information presented to the users via a computing network and each component structured collection of facts being for facts indicating user interaction during a particular time period the method comprising: by a computing system, sampling the plurality of component structured collections of fact records in a deterministic manner across the component structured collections of facts, wherein the sampling includes applying a sampling algorithm to values of a particular eminent attribute of the fact records consistently across the component structured collections of fact records, wherein the algorithm is characterized by deterministically distributing the fact records relative to the eminent attribute, the particular eminent attribute being a dimension of every one of the component structured collections of fact records, by the computing system, forming a merged collection of sampled fact records comprising the fact records sampled from the plurality of component structured collections of fact records, such that the merged collection of sampled fact records is longitudinal for records having the at least one particular eminent attribute value, over multiple time periods; by the computing system, performing an aggregation operation on the merged collection of sampled fact records to determine an aggregation result, the aggregation operates at a same level as the particular eminent attribute value and the aggregation result being an aggregate value representing an aggreate of the facts of the merged collection of sampled fact records; and by the computing system, based on the determined aggregation result and on an indication of characteristics of facts of the sampled fact records relative to the facts of the full structured collection of fact records, determining an indication of a statistical measure of a difference between what would be the result of the aggregation-type operation on the facts of the full structured collection of fact records and the actual result of the aggregation-type operation on facts of the sampled fact records, wherein the indication of the statistical measure of the difference indicates a confidence associated with the result of the aggregation-type operation on the sampled subset of facts. 2. The method of claim 1 , wherein: the indication of confidence is an indication of a confidence interval associated with the result of the aggregation-type operation on the sampled subset of facts. | 0.611328 |
7,707,593 | 6 | 9 | 6. A computer-implemented method of communicating with at least one application program that issues at least one call on a host-environment object on behalf of content for enabling the content to interact with a selected hosting environment, the method comprising: indicating, by a processor, in the content at least one desired interaction with any one of a plurality of hosting environments, wherein the hosting environments include a browser environment and a window environment; and identifying the at least one desired interaction in the content without providing implementation instructions associated with the selected hosting environment; wherein the at least one application program comprises logic for identifying a selected hosting environment by examining a settings module associated with the at least one application program and for referencing the host-environment object that is associated with the selected hosting environment for issuing the at least one call on, wherein indicating and identifying the at least one desired interaction within the content are performed using at least one of either one or more programmatic language statements, one or more declarative language statements, one or more extensible application markup oriented language (XAML) statements, or any other computer language statements, and wherein issuing at least one call on at least one environment object further comprises referencing an object interface that allows the at least one call on the host-environment object to be made on a browser environment object or a window environment object that becomes available when the selected hosting environment is selected. | 6. A computer-implemented method of communicating with at least one application program that issues at least one call on a host-environment object on behalf of content for enabling the content to interact with a selected hosting environment, the method comprising: indicating, by a processor, in the content at least one desired interaction with any one of a plurality of hosting environments, wherein the hosting environments include a browser environment and a window environment; and identifying the at least one desired interaction in the content without providing implementation instructions associated with the selected hosting environment; wherein the at least one application program comprises logic for identifying a selected hosting environment by examining a settings module associated with the at least one application program and for referencing the host-environment object that is associated with the selected hosting environment for issuing the at least one call on, wherein indicating and identifying the at least one desired interaction within the content are performed using at least one of either one or more programmatic language statements, one or more declarative language statements, one or more extensible application markup oriented language (XAML) statements, or any other computer language statements, and wherein issuing at least one call on at least one environment object further comprises referencing an object interface that allows the at least one call on the host-environment object to be made on a browser environment object or a window environment object that becomes available when the selected hosting environment is selected. 9. The computer-implemented method as set forth in claim 6 wherein issuing at least one call on a host-environment object further comprises referencing the host-environment object that represents either a browser-environment object or a window-environment object for issuing the at least one call on. | 0.535604 |
9,503,228 | 10 | 18 | 10. A server implementing an application to detect, diagnose, and mitigate issues in a network, the server comprising: a network interface, a processor, and memory, each communicatively coupled therebetween; wherein the memory stores instructions that, when executed, cause the processor to obtain Operations, Administration, and Maintenance (OAM) data related to the network, the OAM data related to current operation of the network, receive external data related to the network, the external data describing events related to any one or more of construction, weather, natural disasters, and planned outages, instantiate a rule engine to evaluate one or more rules based on any one of the OAM data, an event, policy, and an anomaly, perform one or more actions based on an evaluation of the one or more rules, and analyze the external data to determine a relationship between the events and the network elements in the network, wherein the relationship comprises any one or more of distance, amount of time the event exists, a number of events in a shared area, reputation of an event based on historical data, and a magnitude of collateral damage an event may cause to generate an associated risk level. | 10. A server implementing an application to detect, diagnose, and mitigate issues in a network, the server comprising: a network interface, a processor, and memory, each communicatively coupled therebetween; wherein the memory stores instructions that, when executed, cause the processor to obtain Operations, Administration, and Maintenance (OAM) data related to the network, the OAM data related to current operation of the network, receive external data related to the network, the external data describing events related to any one or more of construction, weather, natural disasters, and planned outages, instantiate a rule engine to evaluate one or more rules based on any one of the OAM data, an event, policy, and an anomaly, perform one or more actions based on an evaluation of the one or more rules, and analyze the external data to determine a relationship between the events and the network elements in the network, wherein the relationship comprises any one or more of distance, amount of time the event exists, a number of events in a shared area, reputation of an event based on historical data, and a magnitude of collateral damage an event may cause to generate an associated risk level. 18. The server of claim 10 , wherein the relationship is determined through: geocoding the events and network elements and calculating the distance based thereon, parsing environmental event consolidation programs for end and start times of an event to calculate a time window, parsing environmental event consolidation programs for historical reputation of an event and assigning a value based on credibility, and parsing environmental event consolidation programs for existence of collateral damage multipliers and assigning a value based thereon. | 0.5 |
8,843,479 | 1 | 3 | 1. A method performed by one or more server devices, the method comprising: identifying, by the one or more server devices, a source that published a document, the source corresponding to an entity that publishes documents; determining, by the one or more server devices, a measure of importance of the source that published the document, determining the measure of importance of the source including: determining that content of the document includes information that is associated with a geographic region, and determining whether the source is associated with a geographic region that matches the geographic region associated with the information included in the content of the document, the measure of importance of the source being determined based on determining whether the source is associated with a geographic region that matches the geographic region associated with the information included in the content of the document, the measure of importance of the source exceeding measure of importance of one or more different sources that publish documents when: the source is associated with a geographic region that matches the geographic region associated with the information included in the content of the document, and the one or more different sources are associated with a geographic region that does not match the geographic region associated with the information included in the content of the document; and ranking, by the one or more server devices, the document against at least one other document, based on one or more factors, the one or more factors including the determined measure of importance of the source, the at least one other document being published by another source. | 1. A method performed by one or more server devices, the method comprising: identifying, by the one or more server devices, a source that published a document, the source corresponding to an entity that publishes documents; determining, by the one or more server devices, a measure of importance of the source that published the document, determining the measure of importance of the source including: determining that content of the document includes information that is associated with a geographic region, and determining whether the source is associated with a geographic region that matches the geographic region associated with the information included in the content of the document, the measure of importance of the source being determined based on determining whether the source is associated with a geographic region that matches the geographic region associated with the information included in the content of the document, the measure of importance of the source exceeding measure of importance of one or more different sources that publish documents when: the source is associated with a geographic region that matches the geographic region associated with the information included in the content of the document, and the one or more different sources are associated with a geographic region that does not match the geographic region associated with the information included in the content of the document; and ranking, by the one or more server devices, the document against at least one other document, based on one or more factors, the one or more factors including the determined measure of importance of the source, the at least one other document being published by another source. 3. The method of claim 1 , where determining the measure of importance of the source further includes: increasing an initial measure of importance of the source to obtain an increased initial measure of importance when the content of the document includes the information associated with the geographic region and when the source is associated with a geographic region that matches the geographic region with which the information is associated, where the increased initial measure of importance of the source corresponds to the determined measure of importance of the source. | 0.5 |
10,122,657 | 1 | 19 | 1. A system comprising: a non-transitory memory; and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising: determining context information associated with a first message received at a communication account of a user, the context information associated with the first message including a dependency of the first message with a second message previously received by the communication account, wherein the first message has a first communication format, and wherein the second message has a second communication format that is different than the first communication format; causing the first message to be displayed in context with the second message on a graphical interface; receiving, via the graphical interface, content for a new message from the user; receiving, via the graphical interface, a communication policy of the new message from the user, wherein the communication policy designates a prior message to send with the new message when the new message is forwarded or quoted in a future communication by a recipient of the new message, and wherein the communication policy designates that the recipient of the new message cannot parse out the prior message from the new message when the new message is forwarded or quoted by the recipient and that a presentation of the new message is based on the recipient; and generating the new message based on the content and the communication policy of the new message. | 1. A system comprising: a non-transitory memory; and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising: determining context information associated with a first message received at a communication account of a user, the context information associated with the first message including a dependency of the first message with a second message previously received by the communication account, wherein the first message has a first communication format, and wherein the second message has a second communication format that is different than the first communication format; causing the first message to be displayed in context with the second message on a graphical interface; receiving, via the graphical interface, content for a new message from the user; receiving, via the graphical interface, a communication policy of the new message from the user, wherein the communication policy designates a prior message to send with the new message when the new message is forwarded or quoted in a future communication by a recipient of the new message, and wherein the communication policy designates that the recipient of the new message cannot parse out the prior message from the new message when the new message is forwarded or quoted by the recipient and that a presentation of the new message is based on the recipient; and generating the new message based on the content and the communication policy of the new message. 19. The system of claim 1 , wherein the new message is sent from the user to a second recipient, and wherein the communication policy of the new message causes the one or more portions of the content to have a first ordering for the recipient and a second ordering for the second recipient, and wherein the second ordering is a rearrangement of the first ordering. | 0.5 |
7,656,861 | 29 | 31 | 29. A system for transporting text in a real-time Internet Protocol (IP) media transport session, comprising: means for receiving text signaling from a network or from a text generation device; means for identifying text characters represented by the text signaling; means for formatting the identified text characters into text packets; and means for sending the text packets over the same real-time IP media transport session used for transporting media packets, wherein the text packets and media packets are assigned shared sequentially increasing packet numbers in a sequential incrementally increasing order that the combination of the test packets and media packets are each sent in the media transport session, wherein: the text signaling includes analog tones representing the text characters; said means for identifying extracts a digital meaning from the analog tones and discards other analog signaling characteristics from the analog tones; said means for formatting converts the identified digital meaning of the analog tones into corresponding digital values that represent the text characters and formats the digital values into a packet payload in one of the text packets; and said means for sending sends the text packets without including the other discarded analog signaling characteristics from the analog tones. | 29. A system for transporting text in a real-time Internet Protocol (IP) media transport session, comprising: means for receiving text signaling from a network or from a text generation device; means for identifying text characters represented by the text signaling; means for formatting the identified text characters into text packets; and means for sending the text packets over the same real-time IP media transport session used for transporting media packets, wherein the text packets and media packets are assigned shared sequentially increasing packet numbers in a sequential incrementally increasing order that the combination of the test packets and media packets are each sent in the media transport session, wherein: the text signaling includes analog tones representing the text characters; said means for identifying extracts a digital meaning from the analog tones and discards other analog signaling characteristics from the analog tones; said means for formatting converts the identified digital meaning of the analog tones into corresponding digital values that represent the text characters and formats the digital values into a packet payload in one of the text packets; and said means for sending sends the text packets without including the other discarded analog signaling characteristics from the analog tones. 31. The system according to claim 29 including means for specifying, in a media-signaling session prior to sending the text packets, a character rate that controls a maximum rate that text characters can be transmitted in text packets during the real-time IP media transport session as a preventative against dropping of text packets. | 0.640086 |
9,037,472 | 1 | 3 | 1. A method for facilitating communications for a user transaction, the method comprising, by a processor and associated memory: determining a goal transaction for a user to provide input to a human-to-machine interface, said determining including analyzing the human-to-machine interface to determine one or more states and one or more navigation paths of a state machine of the human-to-machine interface defining available interactions for the user to interact with the human-to-machine interface and accounting for at least a subset of the states and associating the goal transaction with at least the one or more navigation paths of the state machine, the user reaching at least one end state of the one or more navigation paths via an individual interaction with a visual representation of a voice input parameter, the state machine operating in a manner consistent with the at least the subset of the states; constructing and presenting the visual representation of the voice input parameter for the goal transaction based on at least the subset of the states, the visual representation of the voice input parameter representing multiple operations of the goal transaction optionally available for the user to employ to achieve interaction with the human-to-machine interface in fewer stages than through individual interactions with the human-to-machine interface; and enabling a user interaction with the human-to-machine interface via the visual representation. | 1. A method for facilitating communications for a user transaction, the method comprising, by a processor and associated memory: determining a goal transaction for a user to provide input to a human-to-machine interface, said determining including analyzing the human-to-machine interface to determine one or more states and one or more navigation paths of a state machine of the human-to-machine interface defining available interactions for the user to interact with the human-to-machine interface and accounting for at least a subset of the states and associating the goal transaction with at least the one or more navigation paths of the state machine, the user reaching at least one end state of the one or more navigation paths via an individual interaction with a visual representation of a voice input parameter, the state machine operating in a manner consistent with the at least the subset of the states; constructing and presenting the visual representation of the voice input parameter for the goal transaction based on at least the subset of the states, the visual representation of the voice input parameter representing multiple operations of the goal transaction optionally available for the user to employ to achieve interaction with the human-to-machine interface in fewer stages than through individual interactions with the human-to-machine interface; and enabling a user interaction with the human-to-machine interface via the visual representation. 3. The method of claim 1 wherein determining the goal transaction includes determining the goal transaction based on a plurality of transactions with the human-to-machine interface of a plurality of users. | 0.838328 |
10,055,203 | 8 | 14 | 8. A device, comprising: one or more processors to: receive a state chart generated via a technical computing environment, the state chart including a textual portion and a graphical portion, the state chart including: a first state block, a second state block, and an implicit event command associated with the first state block, and the graphical portion including the implicit event command, the second state block including textual code understood by a textual engine of the technical computing environment; parse the state chart into the textual portion and the graphical portion; initiate execution of the state chart; identify, during the execution of the state chart, the implicit event command, the one or more processors, when identifying the implicit event command, being to: search the state chart for commands that include information associated with implicit event commands, and identify the implicit event command based on searching the state chart; transform the implicit event command, which is not understood by a graphical engine of the technical computing environment, into a transformed implicit event command that is understood by the graphical engine, the one or more processors, when transforming the implicit event command into the transformed implicit event command, being to: provide the implicit event command to a transformer, and transform, with the transformer, the implicit event command into the transformed implicit event command; parse, during the execution of the state chart, the transformed implicit event command to identify an event in the state chart and a command associated with the transformed implicit event command, the transformed implicit event command identifying the event in the state chart without identifying the second state block, the event being associated with an action associated with the first state block, and the transformed implicit event command including a reference to the first state block; receive, during the execution of the state chart, an indication of an occurrence of the action associated with the first state block; and initiate the second state block based on the indication and based on the command, the second state block being initiated without an explicit event command being provided in the second state block. | 8. A device, comprising: one or more processors to: receive a state chart generated via a technical computing environment, the state chart including a textual portion and a graphical portion, the state chart including: a first state block, a second state block, and an implicit event command associated with the first state block, and the graphical portion including the implicit event command, the second state block including textual code understood by a textual engine of the technical computing environment; parse the state chart into the textual portion and the graphical portion; initiate execution of the state chart; identify, during the execution of the state chart, the implicit event command, the one or more processors, when identifying the implicit event command, being to: search the state chart for commands that include information associated with implicit event commands, and identify the implicit event command based on searching the state chart; transform the implicit event command, which is not understood by a graphical engine of the technical computing environment, into a transformed implicit event command that is understood by the graphical engine, the one or more processors, when transforming the implicit event command into the transformed implicit event command, being to: provide the implicit event command to a transformer, and transform, with the transformer, the implicit event command into the transformed implicit event command; parse, during the execution of the state chart, the transformed implicit event command to identify an event in the state chart and a command associated with the transformed implicit event command, the transformed implicit event command identifying the event in the state chart without identifying the second state block, the event being associated with an action associated with the first state block, and the transformed implicit event command including a reference to the first state block; receive, during the execution of the state chart, an indication of an occurrence of the action associated with the first state block; and initiate the second state block based on the indication and based on the command, the second state block being initiated without an explicit event command being provided in the second state block. 14. The device of claim 8 , where the one or more processors are further to: monitor the execution of the state chart; and identify, based on monitoring the execution of the state chart, the implicit event command and information indicating that the implicit event command is associated with the first state block. | 0.5 |
10,003,688 | 1 | 2 | 1. A method of authenticating a telephone caller, the method comprising: receiving, by a processor of an authentication server, audio data including speech of the telephone caller; analyzing, by the processor, the audio data to identify a plurality of words from the speech of the telephone caller and to identify an occurrence frequency for each of the plurality of words; comparing, by the processor, the plurality of words and the occurrence frequencies to a plurality of word clusters, each word cluster comprising a plurality of associated words and an occurrence frequency for each of the plurality of associated words, and each word cluster being associated with one of a plurality of demographics; determining, by the processor, a most similar word cluster of the plurality of word clusters to the audio data based on a similarity of the plurality of words and the plurality of associated words of the most similar cluster and a similarity of the occurrence frequencies of the plurality of words and the occurrence frequencies of the plurality of associated words of the most similar cluster; receiving, by the processor, a purported identity of the telephone caller, the purported identity including caller demographic data; comparing, by the processor, the caller demographic data to the demographic associated with the most similar word cluster; and identifying, by the processor, the telephone caller as at least one of: likely having the purported identity in response to determining the caller demographic data matches the demographic associated with the most similar word cluster, and unlikely to have the purported identity in response to determining the caller demographic data matches a demographic associated with a word cluster different from the most similar word cluster. | 1. A method of authenticating a telephone caller, the method comprising: receiving, by a processor of an authentication server, audio data including speech of the telephone caller; analyzing, by the processor, the audio data to identify a plurality of words from the speech of the telephone caller and to identify an occurrence frequency for each of the plurality of words; comparing, by the processor, the plurality of words and the occurrence frequencies to a plurality of word clusters, each word cluster comprising a plurality of associated words and an occurrence frequency for each of the plurality of associated words, and each word cluster being associated with one of a plurality of demographics; determining, by the processor, a most similar word cluster of the plurality of word clusters to the audio data based on a similarity of the plurality of words and the plurality of associated words of the most similar cluster and a similarity of the occurrence frequencies of the plurality of words and the occurrence frequencies of the plurality of associated words of the most similar cluster; receiving, by the processor, a purported identity of the telephone caller, the purported identity including caller demographic data; comparing, by the processor, the caller demographic data to the demographic associated with the most similar word cluster; and identifying, by the processor, the telephone caller as at least one of: likely having the purported identity in response to determining the caller demographic data matches the demographic associated with the most similar word cluster, and unlikely to have the purported identity in response to determining the caller demographic data matches a demographic associated with a word cluster different from the most similar word cluster. 2. The method of claim 1 , further comprising: analyzing, by the processor, the audio data to identify at least one acoustic characteristic of the speech of the telephone caller; and comparing, by the processor, the at least one acoustic characteristic of the speech of the telephone caller to the plurality of word clusters, each word cluster further comprising at least one associated acoustic characteristic; wherein the determining, by the processor, the most similar word cluster of the plurality of word clusters to the audio data is further based on a similarity of the at least one acoustic characteristic of the speech of the telephone caller and the at least one associated acoustic characteristic of the most similar cluster. | 0.545117 |
7,966,352 | 1 | 15 | 1. A computer-implemented method of capturing and treating content using a computer system having a processor, memory, and data storage subsystems, the computer-implemented method comprising: setting a mode of operation to a content capture mode for interpreting user input for the purpose of selecting an on-screen region of a display, and receiving a path drawn by a user, the path defining boundaries of the selected on-screen region of the display, wherein pixels comprising one or more graphical elements representing a first set of one or more textual characters are displayed in the selected on-screen region; capturing the pixels displayed within the selected on-screen region, and storing the captured pixels in an image file; switching the mode of operation to an annotation mode in response to a user command; receiving an annotation drawn by the user on the display, wherein the received annotation is implemented using a plurality of tools via a toolbar, the toolbar appearing after the selecting an on-screen region; obtaining context information for the one or more graphical elements by automatically applying text recognition to the annotation, and storing the results of the text recognition as context information via the computer system, wherein certain context information comprises preventive measures that limit an association of history with the one or more graphical elements based upon digital rights management licenses, and obtaining additional context information by extracting the first set of one or more textual characters and extracting a second set of textual characters displayed in proximity with the first set, wherein the context information and the additional context information are automatically stored in association with the image file. | 1. A computer-implemented method of capturing and treating content using a computer system having a processor, memory, and data storage subsystems, the computer-implemented method comprising: setting a mode of operation to a content capture mode for interpreting user input for the purpose of selecting an on-screen region of a display, and receiving a path drawn by a user, the path defining boundaries of the selected on-screen region of the display, wherein pixels comprising one or more graphical elements representing a first set of one or more textual characters are displayed in the selected on-screen region; capturing the pixels displayed within the selected on-screen region, and storing the captured pixels in an image file; switching the mode of operation to an annotation mode in response to a user command; receiving an annotation drawn by the user on the display, wherein the received annotation is implemented using a plurality of tools via a toolbar, the toolbar appearing after the selecting an on-screen region; obtaining context information for the one or more graphical elements by automatically applying text recognition to the annotation, and storing the results of the text recognition as context information via the computer system, wherein certain context information comprises preventive measures that limit an association of history with the one or more graphical elements based upon digital rights management licenses, and obtaining additional context information by extracting the first set of one or more textual characters and extracting a second set of textual characters displayed in proximity with the first set, wherein the context information and the additional context information are automatically stored in association with the image file. 15. The computer-implemented method of claim 1 , further comprising: navigating through the second sets of textual characters that reside within the path drawn by the user, and subsequently navigating through any sets of textual characters that reside outside the path drawn by the user. | 0.807383 |
8,606,575 | 8 | 10 | 8. An apparatus, comprising: a receiver configured to receive a plurality of spoken utterances and record them in a database memory; and a processor configured to transcribe at least a portion of the plurality of spoken utterances occurring during a call, automatically assign each of the plurality of spoken utterances with a corresponding set of first classifications, determine a confidence rating associated with each of the plurality of spoken utterances and the assigned set of first classifications, and perform at least one of reclassify the plurality of spoken utterances with new classifications based on at least one additional classification operation, and add the assigned first classifications and the corresponding plurality of spoken utterances to a training data set. | 8. An apparatus, comprising: a receiver configured to receive a plurality of spoken utterances and record them in a database memory; and a processor configured to transcribe at least a portion of the plurality of spoken utterances occurring during a call, automatically assign each of the plurality of spoken utterances with a corresponding set of first classifications, determine a confidence rating associated with each of the plurality of spoken utterances and the assigned set of first classifications, and perform at least one of reclassify the plurality of spoken utterances with new classifications based on at least one additional classification operation, and add the assigned first classifications and the corresponding plurality of spoken utterances to a training data set. 10. The apparatus of claim 8 , wherein the transcribed at least a portion of the plurality of spoken utterances comprises at least one of rejected spoken utterances, low confidence rated spoken utterances and disconfirmed spoken utterances. | 0.671233 |
9,858,525 | 9 | 11 | 9. A method, comprising: receiving an input image; generating candidate segment masks based at least in part on the input image; and performing an initial training operation comprising: ranking the candidate segment masks to generate ranked candidate segment masks; selecting a set of the ranked candidate segment masks to generate a set of the ranked candidate segment masks; selecting a mask of the set of the ranked candidate segment masks as a selected mask; and training a neural network by applying the selected-mask of the set of the ranked candidate segment masks to the neural network. | 9. A method, comprising: receiving an input image; generating candidate segment masks based at least in part on the input image; and performing an initial training operation comprising: ranking the candidate segment masks to generate ranked candidate segment masks; selecting a set of the ranked candidate segment masks to generate a set of the ranked candidate segment masks; selecting a mask of the set of the ranked candidate segment masks as a selected mask; and training a neural network by applying the selected-mask of the set of the ranked candidate segment masks to the neural network. 11. A method as claim 9 recites, wherein the candidate segment masks overlap the ground-truth bounding box at least in part as a degree of overlap. | 0.88964 |
9,104,527 | 8 | 9 | 8. The computer system in accordance with claim 1 , wherein the derived style rule set includes a code style rule set of one or more coded style rules that are set by executing code and wherein a derived style rule description is displayed identifying a derived style rule as one whose values are based on coded values from one or more authored style rules. | 8. The computer system in accordance with claim 1 , wherein the derived style rule set includes a code style rule set of one or more coded style rules that are set by executing code and wherein a derived style rule description is displayed identifying a derived style rule as one whose values are based on coded values from one or more authored style rules. 9. The computer system in accordance with claim 8 , wherein the code is script. | 0.5 |
8,260,604 | 2 | 3 | 2. The method of claim 1 , wherein the first user interface control is a first menu and the second user interface control is a second menu. | 2. The method of claim 1 , wherein the first user interface control is a first menu and the second user interface control is a second menu. 3. The method of claim 2 , further comprising: (h) determining which language is stored as the default language in the user profile, and wherein the presenting (b) comprises presenting the first menu such that the first and second options are listed in the determined language. | 0.565831 |
8,909,579 | 10 | 15 | 10. An apparatus comprising: a processing unit; a proof obtainer operative to obtain a proof of a property with respect to a bounded model having a bounded number of cycles, wherein the bounded model comprising an initial axiom and a transition relation axiom, wherein the proof of the property is a Directed Acyclic Graph (DAG), wherein each non-leaf node of the DAG is deducible from its child nodes, wherein a root of the DAG is the property, and wherein leaves of the DAG are associated with an axiom of the bounded model; a candidate set selector operative to select a set of candidate invariants comprising at least one intermediate node of the DAG; and an invariant determinator operative to determine, without using the proof and using a Boolean satisfiability problem solver, a subset of the set of candidates, wherein the subset comprises invariants which are held in an unbounded model during each cycle after the bound, wherein the unbounded model is an unbounded version of the bounded model. | 10. An apparatus comprising: a processing unit; a proof obtainer operative to obtain a proof of a property with respect to a bounded model having a bounded number of cycles, wherein the bounded model comprising an initial axiom and a transition relation axiom, wherein the proof of the property is a Directed Acyclic Graph (DAG), wherein each non-leaf node of the DAG is deducible from its child nodes, wherein a root of the DAG is the property, and wherein leaves of the DAG are associated with an axiom of the bounded model; a candidate set selector operative to select a set of candidate invariants comprising at least one intermediate node of the DAG; and an invariant determinator operative to determine, without using the proof and using a Boolean satisfiability problem solver, a subset of the set of candidates, wherein the subset comprises invariants which are held in an unbounded model during each cycle after the bound, wherein the unbounded model is an unbounded version of the bounded model. 15. The apparatus of claim 10 , wherein said candidate set selector is operative to add the property as a candidate, wherein said invariant determinator is operative to verify that the property is an invariant. | 0.818339 |
8,935,163 | 10 | 11 | 10. The automatic conversation system according to claim 7 , wherein the conversation server is adapted to send, to the conversation device, operation control information in which an operation to be executed by the conversation device is described; and the conversation device is adapted to execute the operation based on the operation control information along with the output of the reply sentence. | 10. The automatic conversation system according to claim 7 , wherein the conversation server is adapted to send, to the conversation device, operation control information in which an operation to be executed by the conversation device is described; and the conversation device is adapted to execute the operation based on the operation control information along with the output of the reply sentence. 11. The automatic conversation system according to claim 10 , wherein the conversation device is a terminal device that is controlled based on the operation control information. | 0.5 |
9,703,771 | 2 | 4 | 2. The computer system of claim 1 , wherein the data defining computer operating context includes environmental data from a sensor. | 2. The computer system of claim 1 , wherein the data defining computer operating context includes environmental data from a sensor. 4. The computer system of claim 2 , wherein the environmental data includes data indicating a location of a computer. | 0.5 |
8,150,885 | 1 | 4 | 1. A method of cross-referencing data within a searchable database on a computer device including a memory device, wherein a directory tree structure is stored on the memory device and includes nodes and branches comprising links between the nodes, the directory tree structure including a designated category for each node, the method comprising: generating at least two data pointers corresponding to a specific node, wherein a first data pointer of the at least two data pointers points from the specific node to a first item of data within the searchable database via a first navigation path through the directory tree structure, wherein a second data pointer of the at least two data pointers points from the specific node to a second item of data within the searchable database via a second navigation path through the directory tree structure, and wherein the first and second items of data are related to the designated category of the specific node; and generating at least one node pointer, wherein the at least one node pointer points from a first node located in the first navigation path to a second node located in the second navigation path, wherein the first navigation path is different from the second navigation path, wherein the first node and the second node are each different from the specific node; wherein, at each node within the directory tree structure, the searchable database is searchable by selecting any data pointers or node pointers corresponding to the node or by performing one or more of a keyword search, a hierarchical search, a dichotomous key search, and a parametric search. | 1. A method of cross-referencing data within a searchable database on a computer device including a memory device, wherein a directory tree structure is stored on the memory device and includes nodes and branches comprising links between the nodes, the directory tree structure including a designated category for each node, the method comprising: generating at least two data pointers corresponding to a specific node, wherein a first data pointer of the at least two data pointers points from the specific node to a first item of data within the searchable database via a first navigation path through the directory tree structure, wherein a second data pointer of the at least two data pointers points from the specific node to a second item of data within the searchable database via a second navigation path through the directory tree structure, and wherein the first and second items of data are related to the designated category of the specific node; and generating at least one node pointer, wherein the at least one node pointer points from a first node located in the first navigation path to a second node located in the second navigation path, wherein the first navigation path is different from the second navigation path, wherein the first node and the second node are each different from the specific node; wherein, at each node within the directory tree structure, the searchable database is searchable by selecting any data pointers or node pointers corresponding to the node or by performing one or more of a keyword search, a hierarchical search, a dichotomous key search, and a parametric search. 4. The method as claimed in claim 1 , further comprising at least one of adding a node to the directory tree structure, editing a node within the directory tree structure, and deleting a node from the directory tree structure. | 0.727711 |
8,682,811 | 8 | 9 | 8. One or more computer-readable storage media storing information to enable a computing device to perform a process, wherein the computer-readable storage media is not a signal, the process comprising: receiving a clickthrough log comprised of information indicating URLs that were clicked by users when presented in search results, the clickthrough log having been accumulated by a search engine that provided the search results to the users in response to queries from the users, the search engine having an existing index of web pages crawled from the Internet; receiving a list of candidate URLs, the candidate URLs comprising URLs being considered for inclusion in a new index of the web pages crawled from the Internet, each URL identifying a web page on the Internet; training a model and storing the model on the computing device, wherein the model is trained using training data comprised of URLs and information indicating whether the URLs were clicked in a search result of the search engine; selecting a URL from the list of candidate URLs, computing a feature vector of the selected URL by computing features of the URL that are included in the feature vector, the features including a click feature that is based on information from the clickthrough log that indicates whether or how often or how many times the selected URL has been clicked in search results of the search engine; passing the feature vector to the trained model and outputting, according to the trained model, a measure of how likely the selected URL is to be searched in the future by a user submitting a future unknown query to the search engine; using the measure to determine whether to include the selected URL in the new index; and building the new index and providing the new index to the search engine which uses the new index to answer user queries for web pages, wherein the search engine uses the new index by receiving a user query, searching the new index for web pages that match the user query, and when no web pages are found in the new index, using a second index that indexes web pages not indexed in the new index. | 8. One or more computer-readable storage media storing information to enable a computing device to perform a process, wherein the computer-readable storage media is not a signal, the process comprising: receiving a clickthrough log comprised of information indicating URLs that were clicked by users when presented in search results, the clickthrough log having been accumulated by a search engine that provided the search results to the users in response to queries from the users, the search engine having an existing index of web pages crawled from the Internet; receiving a list of candidate URLs, the candidate URLs comprising URLs being considered for inclusion in a new index of the web pages crawled from the Internet, each URL identifying a web page on the Internet; training a model and storing the model on the computing device, wherein the model is trained using training data comprised of URLs and information indicating whether the URLs were clicked in a search result of the search engine; selecting a URL from the list of candidate URLs, computing a feature vector of the selected URL by computing features of the URL that are included in the feature vector, the features including a click feature that is based on information from the clickthrough log that indicates whether or how often or how many times the selected URL has been clicked in search results of the search engine; passing the feature vector to the trained model and outputting, according to the trained model, a measure of how likely the selected URL is to be searched in the future by a user submitting a future unknown query to the search engine; using the measure to determine whether to include the selected URL in the new index; and building the new index and providing the new index to the search engine which uses the new index to answer user queries for web pages, wherein the search engine uses the new index by receiving a user query, searching the new index for web pages that match the user query, and when no web pages are found in the new index, using a second index that indexes web pages not indexed in the new index. 9. One or more computer-readable storage media according to claim 8 , wherein the machine learning based model training is executed. | 0.788462 |
8,327,326 | 9 | 10 | 9. The method as recited in claim 1 , wherein the act of transitioning the editor to an interaction mode for positioning closing code constructs comprises an act of visually augmenting the closing code construct with one or more user-interface controls for moving the closing code construct between the one or more valid positions. | 9. The method as recited in claim 1 , wherein the act of transitioning the editor to an interaction mode for positioning closing code constructs comprises an act of visually augmenting the closing code construct with one or more user-interface controls for moving the closing code construct between the one or more valid positions. 10. The method as recited in claim 9 , wherein the act of receiving a form of user input comprises an act of receiving mouse driven input selecting a user-interface control from among the one or more user-interface controls; and wherein the act of re-positioning the closing code construct comprises an act of moving the closing code construct directly to a valid position, from among the one or more valid positions, in response to the mouse driven input. | 0.5 |
8,874,564 | 1 | 10 | 1. A method for communicating search results, the method comprising: receiving user input from a first user to perform a search of a communications network; performing the search based on the first user input to generate search results; determine whether the search results include content dates for content; determine a publication date of the content for each search result; determine a post data of the content for each search result; displaying the search results and a plurality of selection elements associated with each of the search results, wherein each of the plurality of selection elements is associated with one or more second users separate from the first user and is selectable by the first user to communicate each of the search results to the one or more second users separate from the first user; receiving a user selection of one or more of the plurality of selection elements associated with the one or more second users separate from the first user; and communicating the search results to the associated one or more second users separate from the first user, in response to the user selection. | 1. A method for communicating search results, the method comprising: receiving user input from a first user to perform a search of a communications network; performing the search based on the first user input to generate search results; determine whether the search results include content dates for content; determine a publication date of the content for each search result; determine a post data of the content for each search result; displaying the search results and a plurality of selection elements associated with each of the search results, wherein each of the plurality of selection elements is associated with one or more second users separate from the first user and is selectable by the first user to communicate each of the search results to the one or more second users separate from the first user; receiving a user selection of one or more of the plurality of selection elements associated with the one or more second users separate from the first user; and communicating the search results to the associated one or more second users separate from the first user, in response to the user selection. 10. The method according to claim 1 , further comprising: displaying a contact list to the first user for selecting one or more second users separate from the first user not associated with one of the plurality of selection elements. | 0.5 |
10,037,374 | 28 | 29 | 28. A computer-readable storage medium having computer-executable instructions recorded thereon, wherein executing the computer-executable instructions on one or more processors causes the one or more processors to: receive at least a first data stream from a first device and a second data stream from a second device, wherein the first data stream and the second data stream each include one or more sequenced data items; construct at least a first grammar associated with the first device and a second grammar associated with the second device, wherein the first grammar and the second grammar each comprise a symbol sequence that re-expresses the one or more sequenced data items in the respective data streams received from the first device and the second device; calculate one or more distance metrics that quantify a similarity between the first grammar and the second grammar according to a comparison between one or more rules that represent a repeated pattern in the symbol sequence associated with the first grammar and one or more rules that represent a repeated pattern in the symbol sequence associated with the second grammar; and determine a relationship between the first device and the second device according to the one or more distance metrics. | 28. A computer-readable storage medium having computer-executable instructions recorded thereon, wherein executing the computer-executable instructions on one or more processors causes the one or more processors to: receive at least a first data stream from a first device and a second data stream from a second device, wherein the first data stream and the second data stream each include one or more sequenced data items; construct at least a first grammar associated with the first device and a second grammar associated with the second device, wherein the first grammar and the second grammar each comprise a symbol sequence that re-expresses the one or more sequenced data items in the respective data streams received from the first device and the second device; calculate one or more distance metrics that quantify a similarity between the first grammar and the second grammar according to a comparison between one or more rules that represent a repeated pattern in the symbol sequence associated with the first grammar and one or more rules that represent a repeated pattern in the symbol sequence associated with the second grammar; and determine a relationship between the first device and the second device according to the one or more distance metrics. 29. The computer-readable storage medium recited in claim 28 , wherein the one or more distance metrics include at least one distance metric that quantifies a syntactic similarity between the first grammar and the second grammar. | 0.538306 |
9,472,184 | 6 | 7 | 6. The method of claim 1 , wherein the warning further comprises a phonetic unit type indicator that distinguishes a phonemic cross-language speech recognition problem from a syllabic cross-language speech recognition problem. | 6. The method of claim 1 , wherein the warning further comprises a phonetic unit type indicator that distinguishes a phonemic cross-language speech recognition problem from a syllabic cross-language speech recognition problem. 7. The method of claim 6 , wherein the phonetic unit type indicator comprises the phonemic cross-language speech recognition problem displayed in a first color and the syllabic cross-language speech recognition problem displayed in a second color different from the first color. | 0.5 |
7,961,143 | 13 | 22 | 13. A device to perform ambiguity resolution in a global navigation satellite system, comprising: a receiver configured to receive satellite carrier signals; one or more processors; and memory storing one or more programs configured for execution by the one or more processors, the one or more programs for resolving ambiguities associated with carrier phase measurements of at least some of the carrier signals received from satellites in an identified set of satellites, the one or more programs including: instructions for identifying a set of ambiguities associated with the carrier phase measurements; instructions for estimating integer ambiguities in the set of ambiguities, including determining a best candidate set and a second best candidate set of integer ambiguity values for each of the ambiguities in the set of ambiguities; instructions for determining that the best candidate set of integer ambiguity values fail to meet a discrimination test with respect to the second best candidate set, and upon such determination, removing from the set of ambiguities each ambiguity for which integer ambiguity values in the best candidate set and second best candidate set fail to meet predefined criteria to produce a reduced set of ambiguities; instructions for performing operations to resolve the integer ambiguities in the reduced set of ambiguities; and instructions for generating a result in accordance with the resolved integer ambiguities in the reduced set of ambiguities. | 13. A device to perform ambiguity resolution in a global navigation satellite system, comprising: a receiver configured to receive satellite carrier signals; one or more processors; and memory storing one or more programs configured for execution by the one or more processors, the one or more programs for resolving ambiguities associated with carrier phase measurements of at least some of the carrier signals received from satellites in an identified set of satellites, the one or more programs including: instructions for identifying a set of ambiguities associated with the carrier phase measurements; instructions for estimating integer ambiguities in the set of ambiguities, including determining a best candidate set and a second best candidate set of integer ambiguity values for each of the ambiguities in the set of ambiguities; instructions for determining that the best candidate set of integer ambiguity values fail to meet a discrimination test with respect to the second best candidate set, and upon such determination, removing from the set of ambiguities each ambiguity for which integer ambiguity values in the best candidate set and second best candidate set fail to meet predefined criteria to produce a reduced set of ambiguities; instructions for performing operations to resolve the integer ambiguities in the reduced set of ambiguities; and instructions for generating a result in accordance with the resolved integer ambiguities in the reduced set of ambiguities. 22. The device of claim 13 , wherein the instructions for performing operations to resolve ambiguities in the reduced set of ambiguities include: instructions for estimating integer ambiguities in the reduced set of ambiguities, including determining a best candidate set and a second best candidate set of integer ambiguity values for each of the integer ambiguities in the reduced set of ambiguities; instructions for determining whether the best candidate set of integer ambiguity values for the reduced set of ambiguities meets the discrimination test with respect to the second best candidate set of integer ambiguity values for the reduced set of ambiguities, and if the discrimination test is met, generating a set of result values; and instructions, the execution of which are enabled if the best candidate set of integer ambiguity values for the reduced set of ambiguities fails to meet the discrimination test, for: removing from the reduced set of ambiguities each ambiguity for which integer ambiguity values in the best candidate set and second best candidate set of integer ambiguity values for the reduced set of ambiguities fail to meet the predefined criteria to produce a second reduced set of ambiguities; performing operations to resolve the integer ambiguities in the second reduced set of ambiguities; and generating the output in accordance with a result of the operations performed to resolve the integer ambiguities in the second reduced set of ambiguities. | 0.5 |
7,836,038 | 1 | 19 | 1. A computer-implemented method for automatically extracting and displaying information about a product from a plurality of articles, the method comprising: in response to receiving a search query for a product, searching an index of articles that describe products for sale; identifying, based on the index searching, a plurality of articles from the index of articles that are responsive to the search query; obtaining, based on the search query, at least one price for the product and at least one image of the product from each of the identified articles by: automatically selecting and extracting a price for the product from a first article of the identified articles by: identifying a potential price in the first article; identifying a price signal associated with the identified potential price in the first article; determining, based on a proximity metric, whether the price signal indicates that the identified potential price is an actual price for the product; responsive to a positive determination, automatically extracting the actual price from the first article; automatically selecting and extracting an image for the product from the first article based on the extracted price; repeating the selection and the extraction of prices and images for other identified articles; and displaying, as a combined search result set, prices extracted and images extracted for the product from the identified articles. | 1. A computer-implemented method for automatically extracting and displaying information about a product from a plurality of articles, the method comprising: in response to receiving a search query for a product, searching an index of articles that describe products for sale; identifying, based on the index searching, a plurality of articles from the index of articles that are responsive to the search query; obtaining, based on the search query, at least one price for the product and at least one image of the product from each of the identified articles by: automatically selecting and extracting a price for the product from a first article of the identified articles by: identifying a potential price in the first article; identifying a price signal associated with the identified potential price in the first article; determining, based on a proximity metric, whether the price signal indicates that the identified potential price is an actual price for the product; responsive to a positive determination, automatically extracting the actual price from the first article; automatically selecting and extracting an image for the product from the first article based on the extracted price; repeating the selection and the extraction of prices and images for other identified articles; and displaying, as a combined search result set, prices extracted and images extracted for the product from the identified articles. 19. The method of claim 1 , wherein the price signal comprises a price representation score for the identified potential price that scores the degree to which the identified potential price appears to be an actual price. | 0.882479 |
9,832,195 | 2 | 11 | 2. A system, comprising: one or more processors; and memory storing instructions that, if executed by the one or more processors, cause the system to: receive user input corresponding to operations on a document, the one or more operations causing a change to an overlay of the document, the overlay containing user annotations to the document; transmit an application programming interface call to upload the overlay for the document having an identifier specified in the application programming interface call; receive, from a document management and collaboration system, a second document identifier corresponding to a version of the document which corresponds to the overlay; receive a request for collaboration on the document; obtain the document and the overlay by transmitting a second application programming interface call that specifies the second document identifier; and transmit the obtained document and the overlay to one or more collaborators for collaboration. | 2. A system, comprising: one or more processors; and memory storing instructions that, if executed by the one or more processors, cause the system to: receive user input corresponding to operations on a document, the one or more operations causing a change to an overlay of the document, the overlay containing user annotations to the document; transmit an application programming interface call to upload the overlay for the document having an identifier specified in the application programming interface call; receive, from a document management and collaboration system, a second document identifier corresponding to a version of the document which corresponds to the overlay; receive a request for collaboration on the document; obtain the document and the overlay by transmitting a second application programming interface call that specifies the second document identifier; and transmit the obtained document and the overlay to one or more collaborators for collaboration. 11. The system of claim 2 , wherein the instructions further comprise instructions that, if executed by the one or more processors, cause the system to transmit another application programming interface call that specifies text and document coordinates corresponding to a location of the text in the document to be inserted into the document by the document management and collaboration system. | 0.5 |
8,019,750 | 19 | 20 | 19. The computer storage-medium as recited in claim 15 , further comprising code for determining a cost associated with using the tuned database query. | 19. The computer storage-medium as recited in claim 15 , further comprising code for determining a cost associated with using the tuned database query. 20. The computer storage medium as recited in claim 19 , further comprising code for comparing a cost associated with using the selected database query to the cost associated with using the tuned database query. | 0.5 |
8,761,574 | 1 | 5 | 1. A method for annotating video content for facilitating language learning comprising: identifying one or more objects in a video content; generating one or more language tags for at least one of the one or more objects; and associating the one or more language tags with utilization information; wherein the utilization information comprises display information configured to be used by a user device in the displaying of at least one of the one or more language tags with the video content. | 1. A method for annotating video content for facilitating language learning comprising: identifying one or more objects in a video content; generating one or more language tags for at least one of the one or more objects; and associating the one or more language tags with utilization information; wherein the utilization information comprises display information configured to be used by a user device in the displaying of at least one of the one or more language tags with the video content. 5. The method of claim 1 , wherein the identifying of at least one of the one or more objects in the video content is performed by an object recognition software. | 0.7 |
9,031,863 | 1 | 3 | 1. A computer-implemented method, comprising: collecting user activity information for a plurality of users, wherein the user activity information that has been collected for the plurality of users includes at least one of web pages that have been viewed by the plurality of users, content of the web pages that have been viewed by the plurality of users, advertisements that have been clicked on by the plurality of users, or user search results that have been selected by the plurality of users; generating by a processor a mapping model, wherein generating a mapping model includes mapping each one of a plurality of different user characteristics to a corresponding set of terms based, at least in part, on the user activity information that has been collected for the plurality of users and user profiles of the plurality of users, wherein each set of terms include advertisement terms that are a subset of an advertisement term list, the advertisement term list being separate from the user profiles, wherein the plurality of different user characteristics include a plurality of different categories that represent user interest or expertise in such different categories and/or a plurality of different user demographics; receiving a request for an advertisement to be displayed in a web page that has been requested by a user, wherein the user is associated with one or more user characteristics from the plurality of different user characteristics, the one or more user characteristics including one of the plurality of categories and/or one of the plurality of different user demographics, the one or more user characteristics being indicated by one of the user profiles; using the mapping model, for each one of the one or more user characteristics of the user, obtaining the corresponding set of terms; and providing the obtained terms for selecting one of a plurality of advertisements for displaying via the web page, wherein the advertisement term list is separate from the plurality of advertisements. | 1. A computer-implemented method, comprising: collecting user activity information for a plurality of users, wherein the user activity information that has been collected for the plurality of users includes at least one of web pages that have been viewed by the plurality of users, content of the web pages that have been viewed by the plurality of users, advertisements that have been clicked on by the plurality of users, or user search results that have been selected by the plurality of users; generating by a processor a mapping model, wherein generating a mapping model includes mapping each one of a plurality of different user characteristics to a corresponding set of terms based, at least in part, on the user activity information that has been collected for the plurality of users and user profiles of the plurality of users, wherein each set of terms include advertisement terms that are a subset of an advertisement term list, the advertisement term list being separate from the user profiles, wherein the plurality of different user characteristics include a plurality of different categories that represent user interest or expertise in such different categories and/or a plurality of different user demographics; receiving a request for an advertisement to be displayed in a web page that has been requested by a user, wherein the user is associated with one or more user characteristics from the plurality of different user characteristics, the one or more user characteristics including one of the plurality of categories and/or one of the plurality of different user demographics, the one or more user characteristics being indicated by one of the user profiles; using the mapping model, for each one of the one or more user characteristics of the user, obtaining the corresponding set of terms; and providing the obtained terms for selecting one of a plurality of advertisements for displaying via the web page, wherein the advertisement term list is separate from the plurality of advertisements. 3. The method of claim 1 , wherein the user activity information comprises a plurality of web pages that have been selected by the plurality of users. | 0.814356 |
9,582,737 | 1 | 6 | 1. A method for recognizing a gesture, the method comprising: determining, by a computer system, a first set of metrics to differentiate gestures from among only a first subset of gestures of a plurality of gestures, the first subset of gestures recognizable as valid input in a particular context of a user interface environment of the computer system; receiving, by the computer system, user input that causes a gesture classification context to be applied from a plurality of gesture classification contexts available for a gesture analysis engine, wherein the gesture classification context indicates the first subset of gestures; applying, by the computer system, the gesture classification context to the gesture analysis engine; after applying the gesture classification context, receiving, by the computer system, data indicative of the gesture performed by a user; identifying, by the computer system, using the gesture analysis engine and based on the first set of metrics, the gesture in accordance with the applied gesture classification context, wherein identifying includes identifying the gesture from only the first subset of gestures of the plurality of gestures indicated by the applied gesture classification context while the gesture classification context is applied; determine a second subset of gestures from the plurality of gestures, wherein each gesture of the second subset of gestures is valid in a second gesture classification context; determining, by the computer system, a second set of metrics for the second subset of gestures to differentiate gestures from among only the second subset of gestures, wherein: only the second subset of gestures are eligible to be identified when the second gesture classification context is applied, and at least one gesture of the second subset of gestures is not in the first subset of gestures; receiving, by the computer system, user input that causes the second gesture classification context to be applied to the gesture analysis engine; after applying the second gesture classification context, receiving, by the computer system, data indicative of a second gesture performed by the user; and identifying, by the computer system, based on the second set of metrics, the second gesture in accordance with the applied second gesture classification context, wherein identifying includes identifying the second gesture from only the second subset of gestures indicated by the applied second gesture classification context. | 1. A method for recognizing a gesture, the method comprising: determining, by a computer system, a first set of metrics to differentiate gestures from among only a first subset of gestures of a plurality of gestures, the first subset of gestures recognizable as valid input in a particular context of a user interface environment of the computer system; receiving, by the computer system, user input that causes a gesture classification context to be applied from a plurality of gesture classification contexts available for a gesture analysis engine, wherein the gesture classification context indicates the first subset of gestures; applying, by the computer system, the gesture classification context to the gesture analysis engine; after applying the gesture classification context, receiving, by the computer system, data indicative of the gesture performed by a user; identifying, by the computer system, using the gesture analysis engine and based on the first set of metrics, the gesture in accordance with the applied gesture classification context, wherein identifying includes identifying the gesture from only the first subset of gestures of the plurality of gestures indicated by the applied gesture classification context while the gesture classification context is applied; determine a second subset of gestures from the plurality of gestures, wherein each gesture of the second subset of gestures is valid in a second gesture classification context; determining, by the computer system, a second set of metrics for the second subset of gestures to differentiate gestures from among only the second subset of gestures, wherein: only the second subset of gestures are eligible to be identified when the second gesture classification context is applied, and at least one gesture of the second subset of gestures is not in the first subset of gestures; receiving, by the computer system, user input that causes the second gesture classification context to be applied to the gesture analysis engine; after applying the second gesture classification context, receiving, by the computer system, data indicative of a second gesture performed by the user; and identifying, by the computer system, based on the second set of metrics, the second gesture in accordance with the applied second gesture classification context, wherein identifying includes identifying the second gesture from only the second subset of gestures indicated by the applied second gesture classification context. 6. The method for recognizing the gesture of claim 1 , wherein: determining the second subset of gestures from the plurality of gestures and determining the second set of metrics for the second subset of gestures to differentiate gestures from among only the second subset of gestures occur during creation of a gesture subset database, wherein the gesture subset database comprises gesture classification contexts for multiple subsets of the plurality of gestures. | 0.5 |
7,624,105 | 16 | 17 | 16. A search engine configured to determine whether a selected portion of an input string including a plurality of input characters matches a regular expression including an inexact pattern, the search engine comprising: a microcontroller having an input to receive a microprogram embodying the inexact pattern and comprising a plurality of commands, wherein each command embodies a different portion of the inexact pattern; and a plurality of co-processors coupled to the microcontroller, wherein each co-processor is dedicated to execute a corresponding one of the commands to implement its associated portion of an inexact pattern match operation between the input string and the inexact pattern, wherein the inexact pattern comprises a specified range of instances of selected characters each belonging to a specified set of characters. | 16. A search engine configured to determine whether a selected portion of an input string including a plurality of input characters matches a regular expression including an inexact pattern, the search engine comprising: a microcontroller having an input to receive a microprogram embodying the inexact pattern and comprising a plurality of commands, wherein each command embodies a different portion of the inexact pattern; and a plurality of co-processors coupled to the microcontroller, wherein each co-processor is dedicated to execute a corresponding one of the commands to implement its associated portion of an inexact pattern match operation between the input string and the inexact pattern, wherein the inexact pattern comprises a specified range of instances of selected characters each belonging to a specified set of characters. 17. The search engine of claim 16 , wherein the microcontroller delegates each of the commands to a designated one of the plurality of co-processors. | 0.78343 |
9,606,986 | 11 | 12 | 11. The method of claim 10 , wherein the weight is further based on a probability of the candidate word within a corpus. | 11. The method of claim 10 , wherein the weight is further based on a probability of the candidate word within a corpus. 12. The method of claim 11 , further comprising: determining, using a second language model, the probability of the candidate word within the corpus. | 0.636585 |
9,501,566 | 8 | 10 | 8. A system comprising: a memory; and a processing device coupled with the memory to: receive, from an input device, an input phrase defining an initial scope of a concept search; identify a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determine a relevance score for each of the plurality of concept terms; determine a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; display the set of concept terms at a first section of a graphical user interface (GUI); display the input phrase at a second section of the GUI; receive, from the input device, a selection of a concept term from the set of concept terms; display in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identify one or more of the documents related to the selection of the concept term and the input phrase; display, in a third section of the GUI, a count of the one or more documents related to the selected concept term and the input phrase; receive, from the input device, a selection of an additional concept term from the set of concept terms; identify one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; update the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and display the one or more documents to a user. | 8. A system comprising: a memory; and a processing device coupled with the memory to: receive, from an input device, an input phrase defining an initial scope of a concept search; identify a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determine a relevance score for each of the plurality of concept terms; determine a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; display the set of concept terms at a first section of a graphical user interface (GUI); display the input phrase at a second section of the GUI; receive, from the input device, a selection of a concept term from the set of concept terms; display in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identify one or more of the documents related to the selection of the concept term and the input phrase; display, in a third section of the GUI, a count of the one or more documents related to the selected concept term and the input phrase; receive, from the input device, a selection of an additional concept term from the set of concept terms; identify one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; update the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and display the one or more documents to a user. 10. The system of claim 8 , wherein the processing device is further to: execute a search of the data set to locate the one or more documents based on the selection of the concept term and the input phrase. | 0.748166 |
7,627,550 | 17 | 18 | 17. The computer readable medium of claim 13 , wherein determining a best match pair comprises, for each token of the first attribute, finding a first match pair in the match list, wherein the first match pair comprises the token and the first match pair has a higher score than any other match pair in the match list. | 17. The computer readable medium of claim 13 , wherein determining a best match pair comprises, for each token of the first attribute, finding a first match pair in the match list, wherein the first match pair comprises the token and the first match pair has a higher score than any other match pair in the match list. 18. The computer readable medium of claim 17 , wherein the match pair comprises the token and a second token and determining a best match pair further comprises removing each match pair in the match list comprising the first token or a second token of the first match pair. | 0.5 |
8,645,378 | 12 | 14 | 12. A system according to claim 11 , further comprising: a classification module to classify the at least one uncoded concept by assigning a classification code based on the relationships between the at least one uncoded concept and the similar reference concepts. | 12. A system according to claim 11 , further comprising: a classification module to classify the at least one uncoded concept by assigning a classification code based on the relationships between the at least one uncoded concept and the similar reference concepts. 14. A system according to claim 12 , wherein the classification module provides a confidence level for the classification code of the at least one uncoded concept. | 0.717993 |
9,069,557 | 13 | 17 | 13. A computer-readable storage memory storing computer-executable instructions for executing on a computer system a computer process, the computer process comprising: receiving into memory of a local computing device a description of a plurality of pipeline-connected entities defining a business intelligence application based on a business intelligence document, wherein the business intelligence application is defined and runs on the local computing device, and wherein the plurality of pipeline-connected entities include: a first entity including one or more expressions, the one or more expressions of the first entity designating data of a remote data source and data of the local computing device against which the one or more expressions of the first entity are to be evaluated by the remote data source by transforming the data of the remote data source and data of the local computing device, a second entity including one or more expressions and designating data of the local computing device against which the one or more expressions of the second entity are to be locally evaluated by transforming the data of the local computing device, and a visualization entity including one or more expressions defining a user interface; updating the one or more connected entities in memory based on a remotely computed result of the first entity and a locally computed result of the second entity; and presenting at least one of the remotely computed result of the first entity and the locally computed result of the second entity via the user interface defined by the visualization entity; wherein the description of the plurality of connected entities forms a directed acyclic graph, and wherein independent parts of the business intelligence application are executed in parallel. | 13. A computer-readable storage memory storing computer-executable instructions for executing on a computer system a computer process, the computer process comprising: receiving into memory of a local computing device a description of a plurality of pipeline-connected entities defining a business intelligence application based on a business intelligence document, wherein the business intelligence application is defined and runs on the local computing device, and wherein the plurality of pipeline-connected entities include: a first entity including one or more expressions, the one or more expressions of the first entity designating data of a remote data source and data of the local computing device against which the one or more expressions of the first entity are to be evaluated by the remote data source by transforming the data of the remote data source and data of the local computing device, a second entity including one or more expressions and designating data of the local computing device against which the one or more expressions of the second entity are to be locally evaluated by transforming the data of the local computing device, and a visualization entity including one or more expressions defining a user interface; updating the one or more connected entities in memory based on a remotely computed result of the first entity and a locally computed result of the second entity; and presenting at least one of the remotely computed result of the first entity and the locally computed result of the second entity via the user interface defined by the visualization entity; wherein the description of the plurality of connected entities forms a directed acyclic graph, and wherein independent parts of the business intelligence application are executed in parallel. 17. The one or more computer-readable storage memory of claim 13 wherein the first entity defines an output communicating to an input of another entity of the description, wherein the data value at the output is the remotely computed result. | 0.628086 |
9,690,786 | 10 | 11 | 10. A method for automatically creating one or more hyperlinks within an electronic text file, wherein each hyperlink of the one or more hyperlinks is linked to one or more videos that are contextually relevant to content of the electronic text file, the method comprising: receiving an electronic text file from a content database; analyzing the electronic text file by term weighting words in the electronic text file to identify one or more keywords contextually relevant to the electronic text file; retrieving a plurality of videos from a video database, each video in the plurality of videos associated with one or more metadata identifiers; extracting the one or more metadata identifiers from each video in the plurality of videos; comparing the one or more extracted metadata identifiers with the one or more identified keywords to identify a plurality of matches between the one or more extracted metadata identifiers and the one or more identified keywords; for at least one keyword in the one or more identified keywords: retrieving a storage address in the video database for at least one multimedia video content item associated with the one or more extracted metadata identifiers matched to the respective keyword; associating the storage address for the multimedia video content item with the keyword to generate at least one hyperlink for the keyword; and inserting a keyword hyperlink into the electronic text file, the keyword hyperlink linking the at least one keyword to a display based on the generated hyperlink; storing the electronic text file with the inserted keyword hyperlink in the content database; in response to a request for the electronic text file, sending the electronic text file with the inserted keyword hyperlink to a client device and, prior to receiving a request for the multimedia video content item, copying the multimedia video content item from the video database into a particular memory; responding to a request from the user device for the multimedia video content item by accessing the multimedia video content item from the particular memory. | 10. A method for automatically creating one or more hyperlinks within an electronic text file, wherein each hyperlink of the one or more hyperlinks is linked to one or more videos that are contextually relevant to content of the electronic text file, the method comprising: receiving an electronic text file from a content database; analyzing the electronic text file by term weighting words in the electronic text file to identify one or more keywords contextually relevant to the electronic text file; retrieving a plurality of videos from a video database, each video in the plurality of videos associated with one or more metadata identifiers; extracting the one or more metadata identifiers from each video in the plurality of videos; comparing the one or more extracted metadata identifiers with the one or more identified keywords to identify a plurality of matches between the one or more extracted metadata identifiers and the one or more identified keywords; for at least one keyword in the one or more identified keywords: retrieving a storage address in the video database for at least one multimedia video content item associated with the one or more extracted metadata identifiers matched to the respective keyword; associating the storage address for the multimedia video content item with the keyword to generate at least one hyperlink for the keyword; and inserting a keyword hyperlink into the electronic text file, the keyword hyperlink linking the at least one keyword to a display based on the generated hyperlink; storing the electronic text file with the inserted keyword hyperlink in the content database; in response to a request for the electronic text file, sending the electronic text file with the inserted keyword hyperlink to a client device and, prior to receiving a request for the multimedia video content item, copying the multimedia video content item from the video database into a particular memory; responding to a request from the user device for the multimedia video content item by accessing the multimedia video content item from the particular memory. 11. The method of claim 10 , wherein the electronic text file includes one or more of: an electronic document, a news and other content-related article, a blog posting, a message board posting, a threaded discussion, an email message, a text-based computer-readable file, a HyperText Markup Language (HTML) file, an Extensible HyperText Markup Language (XHTML) file, an Extensible Markup Language (XML) file, or a webpage. | 0.5 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.