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9,524,288 | 1 | 3 |
1. An Fault Tree (FT) diagram generation aid device, comprising: an import portion adapted to obtain a connection relationship of ruled lines and character strings from first data which is data of an FT diagram expressing a tree structure by the ruled lines and the character strings on a sheet of a spreadsheet program, to acquire an event included in the FT diagram and a connection relationship between events from an obtained connection relationship of the ruled lines and the character strings, and to generate second data describing the tree structure of the FT diagram in a markup language based on the event included in the FT diagram and the connection relationship between events; and an editing portion adapted to edit the second data to generate third data describing the tree structure of the edited FT diagram in the markup language, wherein the import portion generates the second data by making a computer: repeatedly execute first processing of setting a specific cell surrounded by a ruled line as a cell to be analyzed, discovering a lower event of the cell to be analyzed by following a ruled line extending on a right side of the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the lower event between a start tag and an end tag of the cell to be analyzed in the second data, and setting a cell of the lower event as a new cell to be analyzed until no additional new lower event is discovered after a cell of a top event is set as a first cell to be analyzed; repeatedly execute second processing of, when no additional new lower event is discovered, discovering a same-rank event of the cell to be analyzed by following a ruled line branching downward from a ruled line extending to a left side from the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the same-rank event in parallel with the element of the cell to be analyzed in the second data, setting the cell of the same-rank event as a new cell to be analyzed, and repeating the first processing until no additional new lower event is discovered, until no additional new same-rank event is discovered; and repeatedly execute third processing of, when no additional new same-rank event is discovered, setting a higher event of the same-rank event discovered immediately before as a new cell to be analyzed, and repeating the second processing until no additional new same-rank event is discovered, until the cell to be analyzed becomes the cell of the top event.
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1. An Fault Tree (FT) diagram generation aid device, comprising: an import portion adapted to obtain a connection relationship of ruled lines and character strings from first data which is data of an FT diagram expressing a tree structure by the ruled lines and the character strings on a sheet of a spreadsheet program, to acquire an event included in the FT diagram and a connection relationship between events from an obtained connection relationship of the ruled lines and the character strings, and to generate second data describing the tree structure of the FT diagram in a markup language based on the event included in the FT diagram and the connection relationship between events; and an editing portion adapted to edit the second data to generate third data describing the tree structure of the edited FT diagram in the markup language, wherein the import portion generates the second data by making a computer: repeatedly execute first processing of setting a specific cell surrounded by a ruled line as a cell to be analyzed, discovering a lower event of the cell to be analyzed by following a ruled line extending on a right side of the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the lower event between a start tag and an end tag of the cell to be analyzed in the second data, and setting a cell of the lower event as a new cell to be analyzed until no additional new lower event is discovered after a cell of a top event is set as a first cell to be analyzed; repeatedly execute second processing of, when no additional new lower event is discovered, discovering a same-rank event of the cell to be analyzed by following a ruled line branching downward from a ruled line extending to a left side from the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the same-rank event in parallel with the element of the cell to be analyzed in the second data, setting the cell of the same-rank event as a new cell to be analyzed, and repeating the first processing until no additional new lower event is discovered, until no additional new same-rank event is discovered; and repeatedly execute third processing of, when no additional new same-rank event is discovered, setting a higher event of the same-rank event discovered immediately before as a new cell to be analyzed, and repeating the second processing until no additional new same-rank event is discovered, until the cell to be analyzed becomes the cell of the top event. 3. The FT diagram generation aid device according to claim 1 , further comprising: a consistency verification portion adapted to verify the second or third data by obtaining a physical quantity of each event from the second or third data and by determining that consistency of the second or third data is not obtained if the physical quantity of a specific event and the physical quantity of a lower event thereof do not share the same unit and the physical quantity of the specific event cannot be expressed by multiplication, division or exponentiation of the unit of the physical quantity of the lower event.
| 0.5 |
9,288,543 | 16 | 17 |
16. The method of claim 11 , wherein the executing further performs: communicating an advertisement to a user with the media content.
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16. The method of claim 11 , wherein the executing further performs: communicating an advertisement to a user with the media content. 17. The method of claim 16 , wherein the executing further performs: selecting the advertisement based at least in part upon the respective profile of the user.
| 0.733333 |
8,903,813 | 1 | 4 |
1. A computer hardware-implemented method of identifying non-synthetic event elements in electronic files, the computer hardware-implemented method comprising: receiving, from a requesting computer, a first set of binary data that describes a synthetic event, wherein the synthetic event is a non-executable descriptor of a set of context-related factors; performing a context-based search of a database of electronic files to identify a relevant electronic file, wherein the relevant electronic file comprises the synthetic event; searching the relevant electronic file for at least one non-synthetic event element, wherein the non-synthetic event element is absent from the synthetic event; in response to determining that the relevant electronic file comprises said at least one non-synthetic event element, transmitting a second set of binary data to the requesting computer, wherein the second set of binary data comprises the relevant electronic file and a description of an identified non-synthetic event element within the relevant electronic file; limiting the context-based search to search only files that are not related to activities that generated the synthetic event, wherein an activity that generated the synthetic event was medical disease research, and wherein the context-based search is limited to searching non-medical literature; and establishing a connection between the synthetic event and non-synthetic event elements found in the non-medical literature.
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1. A computer hardware-implemented method of identifying non-synthetic event elements in electronic files, the computer hardware-implemented method comprising: receiving, from a requesting computer, a first set of binary data that describes a synthetic event, wherein the synthetic event is a non-executable descriptor of a set of context-related factors; performing a context-based search of a database of electronic files to identify a relevant electronic file, wherein the relevant electronic file comprises the synthetic event; searching the relevant electronic file for at least one non-synthetic event element, wherein the non-synthetic event element is absent from the synthetic event; in response to determining that the relevant electronic file comprises said at least one non-synthetic event element, transmitting a second set of binary data to the requesting computer, wherein the second set of binary data comprises the relevant electronic file and a description of an identified non-synthetic event element within the relevant electronic file; limiting the context-based search to search only files that are not related to activities that generated the synthetic event, wherein an activity that generated the synthetic event was medical disease research, and wherein the context-based search is limited to searching non-medical literature; and establishing a connection between the synthetic event and non-synthetic event elements found in the non-medical literature. 4. The computer hardware-implemented method of claim 1 , wherein the synthetic event describes factors related to a user activity, wherein the user activity is diagnosing a medical patient, and wherein the computer hardware-implemented method further comprises: generating a recommendation to perform additional medical tests, on the medical patient, which are related to the identified non-synthetic event element, wherein the synthetic event is a combination of facts about a patient, wherein the facts about the patient include the patient's age, a medical diagnosis of a primary disease currently afflicting the patient, and a list of medications being taken by the patient, wherein the patient's age, the medical diagnosis of the primary disease currently afflicting the patient, and the list of medications being taken by the patient are factors in the set of context-related factors, and wherein a context of the set of context-related factors is the patient being diagnosed for a secondary disease that is caused by the primary disease.
| 0.5 |
4,685,135 | 5 | 6 |
5. The system of claim 4 wherein said allophone rule means has a plurality of allophonic code signals comprising a plurality of allophone rules arranged in respective character sets as determined by the character and the neighboring characters on each side thereof stored in a common section of said read-only-memory for each of the digital characters representative of printed data that may be input to the system.
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5. The system of claim 4 wherein said allophone rule means has a plurality of allophonic code signals comprising a plurality of allophone rules arranged in respective character sets as determined by the character and the neighboring characters on each side thereof stored in a common section of said read-only-memory for each of the digital characters representative of printed data that may be input to the system. 6. The system of claim 5 wherein said plurality of allophonic code signals comprising said plurality of allophone rules define units of speech representative of the digital character sets, each of which is assigned a particular allophonic code signal as determined by the character set.
| 0.5 |
8,498,870 | 5 | 11 |
5. A system according to claim 1 , wherein said ordering application specific ontology comprises an ordering application specific vocabulary.
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5. A system according to claim 1 , wherein said ordering application specific ontology comprises an ordering application specific vocabulary. 11. A system according to claim 5 , wherein said ordering application specific vocabulary comprises codes, terms and identifiers associated with particular medications and sets of medications and with laboratory tests, radiology tests, nursing services and observations, dietary and nutrition services, fluids, drains, dressings, procedures, treatments, infection control, physical and occupational therapy services, admission, discharge and transfer.
| 0.5 |
9,684,701 | 23 | 24 |
23. A system for replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: a processor configured to: receive a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises to: receive credentials of a user; and determine whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally apply the semantic command to the first local version of the database before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises to: forward the received credentials to the master; determine whether the modification would cause a conflict on the master, comprising to: determine whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, perform the modification on the master node; and a memory coupled with the processor, wherein the memory provides the processor with instructions.
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23. A system for replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: a processor configured to: receive a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises to: receive credentials of a user; and determine whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally apply the semantic command to the first local version of the database before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises to: forward the received credentials to the master; determine whether the modification would cause a conflict on the master, comprising to: determine whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, perform the modification on the master node; and a memory coupled with the processor, wherein the memory provides the processor with instructions. 24. A system as recited in claim 23 , wherein if the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node, then the semantic command is not applied to the master node.
| 0.662863 |
7,761,858 | 1 | 9 |
1. A software development tool for compiling a natural language software application based on a set of programming constructs utilized to model semantics of a natural language, the software development tool comprising: a programming language comprising a set of programming constructs for facilitating natural language programming, the set of programming constructs including a plurality of types that correspond to declarative linguistic elements of a linguistic object model, each type of the plurality of types being independent of a particular spoken language, the plurality of types comprising: an entity type derived from an entity base class having data members, properties, and methods, the entity type adapted to model noun phrases and adjective phrases; a frame type derived from a frame base class and adapted to model semantic events including verbs and nouns; a restriction type derived from a restriction base class and adapted to model oblique arguments, modifiers, and other semantic elements, the restriction type to define semantic relationships between entities and constraints on objects derived from the plurality of types, the restriction type adapted to normalize relationship semantics across syntactic representations; a denoter representing a privileged data member to map entity objects instantiated from the entity type to natural language words; and a compiler executable by a processor to receive a software program from a computer readable storage medium, the software program containing instances of the set of programming constructs, the compiler executable by the processor to generate a software application from the instances of the set of programming constructs, the generated software application comprising a natural language software application.
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1. A software development tool for compiling a natural language software application based on a set of programming constructs utilized to model semantics of a natural language, the software development tool comprising: a programming language comprising a set of programming constructs for facilitating natural language programming, the set of programming constructs including a plurality of types that correspond to declarative linguistic elements of a linguistic object model, each type of the plurality of types being independent of a particular spoken language, the plurality of types comprising: an entity type derived from an entity base class having data members, properties, and methods, the entity type adapted to model noun phrases and adjective phrases; a frame type derived from a frame base class and adapted to model semantic events including verbs and nouns; a restriction type derived from a restriction base class and adapted to model oblique arguments, modifiers, and other semantic elements, the restriction type to define semantic relationships between entities and constraints on objects derived from the plurality of types, the restriction type adapted to normalize relationship semantics across syntactic representations; a denoter representing a privileged data member to map entity objects instantiated from the entity type to natural language words; and a compiler executable by a processor to receive a software program from a computer readable storage medium, the software program containing instances of the set of programming constructs, the compiler executable by the processor to generate a software application from the instances of the set of programming constructs, the generated software application comprising a natural language software application. 9. The software development tool of claim 1 further comprising: an object based on a semantic model, the object adapted to decide whether to accept a property on the object.
| 0.829389 |
8,370,342 | 9 | 15 |
9. A computer-implemented method comprising: transmitting, by a computing device to a server system, a search query that includes multiple search query terms; receiving, by the computing device from the server system, a list of search results that identify a plurality of documents that the server system determined are relevant to the search query terms; receiving, by the computing device, first user input selecting a first search result from the list of search results, the selection of the first search result including a selection of a link that is associated with a first document rather than a sub-page of the first document; transmitting, by the computing device to the server system, an indication of the first search result as having been selected by a user of the computing device, so as to cause the server system to: divide the first document from the plurality of documents that corresponds to the first search result into multiple sub-pages, determine a score for each of the multiple sub-pages based at least on presence of the search query terms in the sub-pages, identify a first sub-page that is determined to be most relevant to the search query from among the sub-pages based on the scores for the sub-pages, and identify a second sub-page that is determined to be next most relevant to the search query from among the sub-pages based on the scores for the sub-pages; presenting, by the computing device to a user of the computing device, the first sub-page; displaying by the computing device as part of the first sub-page a control for replacing the display of the first sub-page with a display of the second sub-page upon user selection of the control; receiving, by the computing device, second user input that requests navigation from the first sub-page to the next most relevant sub-page, wherein user selection of the control causes the received second user input; and presenting, by the computing device to a user of the computing device in response to receiving the second user input, the second sub-page.
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9. A computer-implemented method comprising: transmitting, by a computing device to a server system, a search query that includes multiple search query terms; receiving, by the computing device from the server system, a list of search results that identify a plurality of documents that the server system determined are relevant to the search query terms; receiving, by the computing device, first user input selecting a first search result from the list of search results, the selection of the first search result including a selection of a link that is associated with a first document rather than a sub-page of the first document; transmitting, by the computing device to the server system, an indication of the first search result as having been selected by a user of the computing device, so as to cause the server system to: divide the first document from the plurality of documents that corresponds to the first search result into multiple sub-pages, determine a score for each of the multiple sub-pages based at least on presence of the search query terms in the sub-pages, identify a first sub-page that is determined to be most relevant to the search query from among the sub-pages based on the scores for the sub-pages, and identify a second sub-page that is determined to be next most relevant to the search query from among the sub-pages based on the scores for the sub-pages; presenting, by the computing device to a user of the computing device, the first sub-page; displaying by the computing device as part of the first sub-page a control for replacing the display of the first sub-page with a display of the second sub-page upon user selection of the control; receiving, by the computing device, second user input that requests navigation from the first sub-page to the next most relevant sub-page, wherein user selection of the control causes the received second user input; and presenting, by the computing device to a user of the computing device in response to receiving the second user input, the second sub-page. 15. The computer-implemented method of claim 9 , wherein the second sub-page is immediately provided upon the second user input without additional user input subsequent to the second user input.
| 0.821691 |
8,387,029 | 14 | 21 |
14. A method for parsing and executing a software program, the method comprising: receiving a portion of the software program in an original linguistic form in a high level language, wherein the portion of the software program includes a nonlinear program element having a body; and tokenizing the portion of the software program to generate an input stream of tokens representing the portion of the software program; while retaining the original linguistic form of the software program, using a set of one or more production rules by a parser to directly execute the nonlinear program element by manipulating a parse state and the input stream of tokens representing the body of the nonlinear program element, wherein the one or more production rules include a type conversion production rule useable by the parser to perform type conversion and production rules useable by the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein directly executing comprises executing tokens until the dynamic end of the nonlinear program element is reached, and wherein manipulating the input stream of tokens comprises using the type conversion production rule to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions to skip tokens during execution of the nonlinear program element.
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14. A method for parsing and executing a software program, the method comprising: receiving a portion of the software program in an original linguistic form in a high level language, wherein the portion of the software program includes a nonlinear program element having a body; and tokenizing the portion of the software program to generate an input stream of tokens representing the portion of the software program; while retaining the original linguistic form of the software program, using a set of one or more production rules by a parser to directly execute the nonlinear program element by manipulating a parse state and the input stream of tokens representing the body of the nonlinear program element, wherein the one or more production rules include a type conversion production rule useable by the parser to perform type conversion and production rules useable by the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein directly executing comprises executing tokens until the dynamic end of the nonlinear program element is reached, and wherein manipulating the input stream of tokens comprises using the type conversion production rule to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions to skip tokens during execution of the nonlinear program element. 21. The method as recited in claim 14 , wherein the nonlinear program element comprises an exception handler having a try clause and a catch clause, the process further comprising: marking the beginning of the try clause in the parse stack; and upon detection of exception in the try clause, finding the mark point in the parse stack for the exception handler and discarding all tokens up to the end of the try clause.
| 0.5 |
9,619,564 | 10 | 11 |
10. A system for providing recommended terms, comprising: at least one processor configured to: determine a search query input by a user and an input time point when the search query was input; determine whether the input time point falls within a time range preset within a current time period; in the event that the input time point falls within the time range preset within the current time period, determine whether the search query input is present in a word bank preset for the time range; in the event that the search query input is present in the word bank, provide the user with a special event recommended term preset for the time range; in response to the user selecting the special event recommended term, jump to a special event page preset for the time range; and preset the word bank for the time range, comprising: determine in advance within a previous time period a corresponding time point corresponding to a designated time point within the time range; divide a first set interval prior to the corresponding time point within the previous time period into a plurality of first sub-intervals; for a first sub-interval, determine search queries searched within the plurality of first sub-intervals as unfinalized search queries, and select a first set quantity of unfinalized search queries from the unfinalized search queries in the plurality of first sub-intervals sorted in order of greater to lesser search frequency; determine a second set interval, the corresponding time point being an average time point of the second set interval, the second set interval relating to the corresponding time point; divide the second set interval equally into a plurality of second sub-intervals; for a selected unfinalized search query, determine past search frequencies of unfinalized search queries of the selected first set quantity of the unfinalized search queries within the plurality of second sub-intervals, and determine whether the past search frequencies of the unfinalized search queries in the plurality of second sub-intervals satisfy a normal distribution; in the event that the past search frequencies of the unfinalized search query in the plurality of second sub-intervals satisfy the normal distribution, add the unfinalized search query to the word bank preset for the time range; and in the event that the past search frequencies of the unfinalized search query in the plurality of second sub-intervals do not satisfy the normal distribution, omit adding the unfinalized search query to the word bank preset for the time range; and a memory coupled to the at least one processor and configured to provide the at least one processor with instructions.
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10. A system for providing recommended terms, comprising: at least one processor configured to: determine a search query input by a user and an input time point when the search query was input; determine whether the input time point falls within a time range preset within a current time period; in the event that the input time point falls within the time range preset within the current time period, determine whether the search query input is present in a word bank preset for the time range; in the event that the search query input is present in the word bank, provide the user with a special event recommended term preset for the time range; in response to the user selecting the special event recommended term, jump to a special event page preset for the time range; and preset the word bank for the time range, comprising: determine in advance within a previous time period a corresponding time point corresponding to a designated time point within the time range; divide a first set interval prior to the corresponding time point within the previous time period into a plurality of first sub-intervals; for a first sub-interval, determine search queries searched within the plurality of first sub-intervals as unfinalized search queries, and select a first set quantity of unfinalized search queries from the unfinalized search queries in the plurality of first sub-intervals sorted in order of greater to lesser search frequency; determine a second set interval, the corresponding time point being an average time point of the second set interval, the second set interval relating to the corresponding time point; divide the second set interval equally into a plurality of second sub-intervals; for a selected unfinalized search query, determine past search frequencies of unfinalized search queries of the selected first set quantity of the unfinalized search queries within the plurality of second sub-intervals, and determine whether the past search frequencies of the unfinalized search queries in the plurality of second sub-intervals satisfy a normal distribution; in the event that the past search frequencies of the unfinalized search query in the plurality of second sub-intervals satisfy the normal distribution, add the unfinalized search query to the word bank preset for the time range; and in the event that the past search frequencies of the unfinalized search query in the plurality of second sub-intervals do not satisfy the normal distribution, omit adding the unfinalized search query to the word bank preset for the time range; and a memory coupled to the at least one processor and configured to provide the at least one processor with instructions. 11. The system as described in claim 10 , wherein the determining of whether the past search frequencies of the unfinalized search query in the second sub-intervals satisfy the normal distribution comprises: in the event that a quantity of divided second sub-intervals is not greater than a second set quantity of unfinalized search queries, determine whether the past search frequencies of the unfinalized search query in the second sub-intervals satisfy a normal distribution based on a W-test; and in the event that the quantity of divided second sub-intervals is greater than the second set quantity of unfinalized search queries, determine whether the past search frequencies of the unfinalized search query in the second sub-intervals satisfy a normal distribution based on a D-test.
| 0.5 |
9,396,443 | 15 | 18 |
15. A method, comprising: employing a processor that facilitates execution of computer executable instructions stored on a non-transitory computer readable medium to implement operations, comprising: generating a set of candidate process models based on process data associated with one or more fabrication tools; generating a quality value for each candidate process model in the set of candidate process models; selecting a particular process model from the set of candidate process models based on the quality value associated with each candidate process model in the set of candidate process models; generating a set of candidate solutions associated with the particular process model; and selecting a particular solution from the set of candidate solutions based on a target output value and an output value associated with the particular solution.
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15. A method, comprising: employing a processor that facilitates execution of computer executable instructions stored on a non-transitory computer readable medium to implement operations, comprising: generating a set of candidate process models based on process data associated with one or more fabrication tools; generating a quality value for each candidate process model in the set of candidate process models; selecting a particular process model from the set of candidate process models based on the quality value associated with each candidate process model in the set of candidate process models; generating a set of candidate solutions associated with the particular process model; and selecting a particular solution from the set of candidate solutions based on a target output value and an output value associated with the particular solution. 18. The method of claim 15 , further comprising: generating a quality value and a diversity value for each candidate solution in the set of candidate solutions.
| 0.5 |
8,550,299 | 1 | 12 |
1. A toothpaste dispenser having an appearance of a character, the toothpaste dispenser comprising: a base; a support extending from a first end essentially vertically from the base; and a toothpaste tube holder located at a second end of the support opposite the first end, the toothpaste tube holder capable of being removably coupled to a toothpaste tube, wherein the base comprises a plurality of indentations therein each to receive a first end of a toothbrush and the toothpaste holder comprises a plurality of hooks each correspondingly located thereon to receive a second end of the toothbrush, the toothpaste tube comprises at least one of facial and body features, the dispenser comprising a plurality of toothbrushes, each having a shape of the character's leg, the indentations and hooks located on the dispenser for the toothbrushes to appear as legs extending from the toothpaste tube.
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1. A toothpaste dispenser having an appearance of a character, the toothpaste dispenser comprising: a base; a support extending from a first end essentially vertically from the base; and a toothpaste tube holder located at a second end of the support opposite the first end, the toothpaste tube holder capable of being removably coupled to a toothpaste tube, wherein the base comprises a plurality of indentations therein each to receive a first end of a toothbrush and the toothpaste holder comprises a plurality of hooks each correspondingly located thereon to receive a second end of the toothbrush, the toothpaste tube comprises at least one of facial and body features, the dispenser comprising a plurality of toothbrushes, each having a shape of the character's leg, the indentations and hooks located on the dispenser for the toothbrushes to appear as legs extending from the toothpaste tube. 12. The toothpaste dispenser of claim 1 , wherein the base comprises a communication system operable to track and communicate to a user at least one of time spent brushing and a number of times teeth were brushed.
| 0.596591 |
8,701,004 | 8 | 11 |
8. Apparatus for executing a software application relating to an audio-visual presentation, wherein the audio-visual presentation is one of a plurality of titles stored on a first storage medium, the apparatus comprising means for detecting a title selection request; means for reading data from the first storage medium, the data comprising files with audio-visual presentation data and software application data, the software application data having a language label associated, wherein the means for reading data from the first storage medium operates in response to the detection of a title selection request in said means for detecting a title selection request; means for generating or updating a virtual file system based on the files and software application data read from the first storage medium; means for comparing the language label associated with the read software application data with a preferred language identifier within said virtual file system; means for selecting within said virtual file system software application data that are associated with a language label matching the preferred language identifier; caching means for caching the selected software application data that are associated with a language label matching the preferred language identifier; means for generating first audio-visual presentation from said audio-visual presentation data upon said virtual file system being generated or updated, wherein the first audio-visual presentation starts automatically while said caching means caches the selected software application data, and for generating a second audio-visual presentation after said caching means cached the selected software application data; means for executing a software application based on the cached data while generating said second audio-visual presentation, wherein the software application is distinct from the audio-visual presentation and the software application modifies the audio-visual presentation, and wherein said title selection request refers to the title of the second audio-visual presentation.
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8. Apparatus for executing a software application relating to an audio-visual presentation, wherein the audio-visual presentation is one of a plurality of titles stored on a first storage medium, the apparatus comprising means for detecting a title selection request; means for reading data from the first storage medium, the data comprising files with audio-visual presentation data and software application data, the software application data having a language label associated, wherein the means for reading data from the first storage medium operates in response to the detection of a title selection request in said means for detecting a title selection request; means for generating or updating a virtual file system based on the files and software application data read from the first storage medium; means for comparing the language label associated with the read software application data with a preferred language identifier within said virtual file system; means for selecting within said virtual file system software application data that are associated with a language label matching the preferred language identifier; caching means for caching the selected software application data that are associated with a language label matching the preferred language identifier; means for generating first audio-visual presentation from said audio-visual presentation data upon said virtual file system being generated or updated, wherein the first audio-visual presentation starts automatically while said caching means caches the selected software application data, and for generating a second audio-visual presentation after said caching means cached the selected software application data; means for executing a software application based on the cached data while generating said second audio-visual presentation, wherein the software application is distinct from the audio-visual presentation and the software application modifies the audio-visual presentation, and wherein said title selection request refers to the title of the second audio-visual presentation. 11. Apparatus according to claim 8 , wherein all language-dependent software application data stored in said caching means are associated with the same language label.
| 0.840952 |
9,491,143 | 1 | 8 |
1. A method comprising: receiving, by a first stage of a context-aware pattern matching and parsing (CPMP) hardware accelerator of a network device, a packet stream; performing, by the first stage, a pre-matching process, including string matching and overflow pattern matching, on packets within the packet stream to identify a candidate packet within the packet stream that matches one or more strings or over-flow patterns associated with a set of Intrusion Prevention System (IPS) or Application Delivery Controller (ADC) rules; identifying, by the first stage, a candidate rule from the set of IPS or ADC rules based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching token within the candidate packet; performing, by a second stage of the CPMP hardware accelerator including a plurality of CPMP processors, a full-match process on the candidate packet to determine whether the candidate packet satisfies the candidate rule by fetching and executing special purpose CPMP instructions to perform one or more of (i) context-aware pattern matching on one or more packet field values of the candidate packet, (ii) context-aware string matching on packet data of the candidate packet and (iii) regular expression matching on the packet data based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network device.
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1. A method comprising: receiving, by a first stage of a context-aware pattern matching and parsing (CPMP) hardware accelerator of a network device, a packet stream; performing, by the first stage, a pre-matching process, including string matching and overflow pattern matching, on packets within the packet stream to identify a candidate packet within the packet stream that matches one or more strings or over-flow patterns associated with a set of Intrusion Prevention System (IPS) or Application Delivery Controller (ADC) rules; identifying, by the first stage, a candidate rule from the set of IPS or ADC rules based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching token within the candidate packet; performing, by a second stage of the CPMP hardware accelerator including a plurality of CPMP processors, a full-match process on the candidate packet to determine whether the candidate packet satisfies the candidate rule by fetching and executing special purpose CPMP instructions to perform one or more of (i) context-aware pattern matching on one or more packet field values of the candidate packet, (ii) context-aware string matching on packet data of the candidate packet and (iii) regular expression matching on the packet data based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network device. 8. The method of claim 1 , wherein said performing, by the first stage, a pre-matching process further comprises performing symbol content address memory matching.
| 0.803614 |
9,674,132 | 12 | 13 |
12. A computer system for managing message communications, comprising: a storage media configured to store message objects including emails, chats, SMS, and other type of messages and software modules; a user interface configured to display message contents, and information about message senders or recipients; and one or more processors configured to access a memory module and the storage media, coupled with the user interface, and further configured to invoke a software module on a server or client computing device to (a) receive a first message, wherein the first message is addressed to or received by multiple recipients, (b) register a user action to reply to the first message, (c) display an message composition or editing interface in response to the user action, (d) detect whether the user is replying only to the sender of the first message as a first operation mode, or to multiple recipients of the first message as a second operation mode, and (e) display a notification, wherein the notification indicates whether the user is replying in the first operation mode or in the second operation mode.
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12. A computer system for managing message communications, comprising: a storage media configured to store message objects including emails, chats, SMS, and other type of messages and software modules; a user interface configured to display message contents, and information about message senders or recipients; and one or more processors configured to access a memory module and the storage media, coupled with the user interface, and further configured to invoke a software module on a server or client computing device to (a) receive a first message, wherein the first message is addressed to or received by multiple recipients, (b) register a user action to reply to the first message, (c) display an message composition or editing interface in response to the user action, (d) detect whether the user is replying only to the sender of the first message as a first operation mode, or to multiple recipients of the first message as a second operation mode, and (e) display a notification, wherein the notification indicates whether the user is replying in the first operation mode or in the second operation mode. 13. The system of claim 12 , wherein it is detected that the user is replying only to the sender of the first message, or is replying in the first operation mode, wherein the notification notifies the user that the message being composed will not be sent to multiple recipients of the first message, or will be sent to only the sender of the first message.
| 0.692573 |
7,886,286 | 1 | 4 |
1. A component-based system on at least one computer system, wherein the component-based system allows legacy components to locate necessary artifacts, the component-based system comprising: a processor; a context finder that is installed as a context classloader, wherein the context finder analyzes an execution stack to identify a classloader of a legacy component that initiated a context classloader call during runtime; and a buddy loading system that determines whether the legacy component requires loading at least one buddy to locate an artifact that cannot be found with a normal delegation model, and the buddy loading system locates and loads the at least one buddy using a predefined policy, wherein the at least one buddy comprises a class or a resource component for locating the artifact for the legacy component, and wherein a requirement of buddy loading is determined by examining a mark-up comprising a descriptor that indicates the legacy component requires at least one buddy, and indicates the predefined policy used to locate the at least one buddy, and wherein the predefined policy includes one of the following: a dependent policy, a named policy, a global policy, and an execution stack policy.
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1. A component-based system on at least one computer system, wherein the component-based system allows legacy components to locate necessary artifacts, the component-based system comprising: a processor; a context finder that is installed as a context classloader, wherein the context finder analyzes an execution stack to identify a classloader of a legacy component that initiated a context classloader call during runtime; and a buddy loading system that determines whether the legacy component requires loading at least one buddy to locate an artifact that cannot be found with a normal delegation model, and the buddy loading system locates and loads the at least one buddy using a predefined policy, wherein the at least one buddy comprises a class or a resource component for locating the artifact for the legacy component, and wherein a requirement of buddy loading is determined by examining a mark-up comprising a descriptor that indicates the legacy component requires at least one buddy, and indicates the predefined policy used to locate the at least one buddy, and wherein the predefined policy includes one of the following: a dependent policy, a named policy, a global policy, and an execution stack policy. 4. The component-based system of claim 1 , wherein the dependent policy searches all components that depend on the legacy component marked as requiring buddy loading, and stops when a result is found.
| 0.621212 |
9,330,087 | 1 | 4 |
1. A computer-implemented process, comprising: receiving a parallel corpus of a source language and a target language; applying a machine translation training process to the parallel corpus to generate a cross-lingual phrase table comprising a plurality of source language phrases, each source language phrase having at least one target language translation; applying a blocking operation to the cross-lingual phrase table to group phrases of the source language into blocks by searching the cross-lingual phrase table to find blocks of two or more source language phrases that share similar translations in the target language; searching each of the different source language phrases in each block to identify a stem of a word of the source language, the stem in each block comprising a same sequence of characters occurring in each of the different source language phrases of that block; searching each of the different source language phrases in each block to find a plurality of affixes of the stem of that block, each affix in each block comprising a sequence of characters preceding or following the characters comprising the stem in any of the different source language phrases in that block; generating a set of morphemes comprising the stems and affixes of words of the source language; in response to receipt of a user query in the source language, applying the set of morphemes to automatically create one or more different forms of one or more words of the user query; and performing an expanded query search using the automatically created different forms of the words of the user query.
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1. A computer-implemented process, comprising: receiving a parallel corpus of a source language and a target language; applying a machine translation training process to the parallel corpus to generate a cross-lingual phrase table comprising a plurality of source language phrases, each source language phrase having at least one target language translation; applying a blocking operation to the cross-lingual phrase table to group phrases of the source language into blocks by searching the cross-lingual phrase table to find blocks of two or more source language phrases that share similar translations in the target language; searching each of the different source language phrases in each block to identify a stem of a word of the source language, the stem in each block comprising a same sequence of characters occurring in each of the different source language phrases of that block; searching each of the different source language phrases in each block to find a plurality of affixes of the stem of that block, each affix in each block comprising a sequence of characters preceding or following the characters comprising the stem in any of the different source language phrases in that block; generating a set of morphemes comprising the stems and affixes of words of the source language; in response to receipt of a user query in the source language, applying the set of morphemes to automatically create one or more different forms of one or more words of the user query; and performing an expanded query search using the automatically created different forms of the words of the user query. 4. The computer-implemented process of claim 1 wherein the blocking operation further comprises finding similar target language translations by finding target language translations comprising at least one identical single word.
| 0.568441 |
9,306,941 | 1 | 6 |
1. A system for allowing a plurality of user devices to connect to share, view, edit, mark, and save documents over a local network, the system comprising: a router configured to create the local network between the plurality of user devices, the plurality of user devices comprising a leader device authenticated by the router and one or more participant devices approved by the leader device to join the local network; a document storage device connected to the router and containing thereon one or more documents; wherein the router and the document storage device are configured to provide access to the one or more documents contained on the document storage device when an application installed on the plurality of user devices is run, the application configured to provide a leader graphical user interface (GUI) on the leader device for allowing leader manipulation of at least one of the one or more documents and sharing of at least one of the one or more documents, and a participant GUI on the one or more participant devices for allowing participant manipulation of at least one of the shared documents; wherein the participant GUI is based upon one or more predefined participant types, each participant type provided with a specified functionality in a corresponding participant GUI; wherein a first predefined participant type comprises a court reporter, wherein a corresponding court reporter GUI comprises one or more windows for customizing exhibit stickers, saving exhibit stickers, marking and saving one or more of the at least one of the shared documents, and sharing one or more of the at least one of the shared documents; and wherein a second predefined participant type comprises a guest user, wherein a corresponding guest user GUI comprises one or more windows for selecting, editing, saving, sharing, downloading, and viewing one or more of the at least one of the shared documents.
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1. A system for allowing a plurality of user devices to connect to share, view, edit, mark, and save documents over a local network, the system comprising: a router configured to create the local network between the plurality of user devices, the plurality of user devices comprising a leader device authenticated by the router and one or more participant devices approved by the leader device to join the local network; a document storage device connected to the router and containing thereon one or more documents; wherein the router and the document storage device are configured to provide access to the one or more documents contained on the document storage device when an application installed on the plurality of user devices is run, the application configured to provide a leader graphical user interface (GUI) on the leader device for allowing leader manipulation of at least one of the one or more documents and sharing of at least one of the one or more documents, and a participant GUI on the one or more participant devices for allowing participant manipulation of at least one of the shared documents; wherein the participant GUI is based upon one or more predefined participant types, each participant type provided with a specified functionality in a corresponding participant GUI; wherein a first predefined participant type comprises a court reporter, wherein a corresponding court reporter GUI comprises one or more windows for customizing exhibit stickers, saving exhibit stickers, marking and saving one or more of the at least one of the shared documents, and sharing one or more of the at least one of the shared documents; and wherein a second predefined participant type comprises a guest user, wherein a corresponding guest user GUI comprises one or more windows for selecting, editing, saving, sharing, downloading, and viewing one or more of the at least one of the shared documents. 6. The system of claim 1 , wherein participant manipulation of the at least one of the shared documents comprises one or more of selecting, editing, annotating, saving, downloading, and viewing the at least one of the shared documents.
| 0.502119 |
8,499,283 | 8 | 12 |
8. A system executed by a processor for protecting client computers; comprising: an initial filter that gathers scripting-language-data from webpage data; a signature database of signatures of known scripting-language-data exploits; a parser that generates a parse tree from the scripting-language-data; a normalization and signature matching component that reduces a complexity of the parse tree, generates a representation of at least a portion of a structure of the parse tree, and prevents the scripting-language-data from reaching an intended recipient when the representation matches one of the signatures of known scripting-language-data exploits; and an analysis component that identifies characteristics of the scripting-language-data, scores the characteristics of scripting-language-data based upon a likelihood that the characteristics of the scripting-language-data are associated with malicious scripting-language data, and determines whether to block the scripting-language-data from reaching the intended recipient based upon a score of characteristics of a normalized scripting-language-data and a score of characteristics of inspection data based on the scripting language-data.
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8. A system executed by a processor for protecting client computers; comprising: an initial filter that gathers scripting-language-data from webpage data; a signature database of signatures of known scripting-language-data exploits; a parser that generates a parse tree from the scripting-language-data; a normalization and signature matching component that reduces a complexity of the parse tree, generates a representation of at least a portion of a structure of the parse tree, and prevents the scripting-language-data from reaching an intended recipient when the representation matches one of the signatures of known scripting-language-data exploits; and an analysis component that identifies characteristics of the scripting-language-data, scores the characteristics of scripting-language-data based upon a likelihood that the characteristics of the scripting-language-data are associated with malicious scripting-language data, and determines whether to block the scripting-language-data from reaching the intended recipient based upon a score of characteristics of a normalized scripting-language-data and a score of characteristics of inspection data based on the scripting language-data. 12. The system of claim 8 , wherein the normalized scripting-language-data comprises consolidated portions of scripting-language-data that are normalized into tokens; and wherein the inspection data is collected during the emulated execution of data suspected of being scripting-language-based.
| 0.635236 |
6,124,864 | 21 | 22 |
21. A method as in claim 1 additionally comprising the step of: storing a light model data object in the scene model wherein the light model data object defines at least one parameter of a light that was used to generate the visual image sequence.
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21. A method as in claim 1 additionally comprising the step of: storing a light model data object in the scene model wherein the light model data object defines at least one parameter of a light that was used to generate the visual image sequence. 22. A method as in claim 21 wherein the light model defines at least one light parameter taken from the group consisting of light position, light movement, light intensity, light color, and light orientation.
| 0.5 |
9,679,561 | 11 | 13 |
11. A system comprising: a processor; and a computer-readable storage medium having instruction stored which, when executed by the processor, result in the processor performing operations comprising: receiving speech from a user as part of a speech dialog between the user and a speech recognition service; identifying, based on the speech, a speech pattern of the user; identifying, based on the speech pattern of the user, a plurality of speech recognition models stored in a cloud computing storage environment, each speech recognition model of the plurality of speech recognition models being from a respective speech recognition domain; combining the plurality of speech recognition models, to yield a multi-domain combined speech recognition model; identifying in the speech a specific speech recognition domain, wherein the specific speech recognition domain does not match a specific speech recognition model in the plurality of speech recognition models; receiving sample data associated with the specific speech recognition domain, wherein the sample data is independent of the speech dialog between the user and the speech recognition service; when the sample data is more than a minimum threshold, generating a new domain-specific speech recognition model for the specific speech recognition domain; and when sample data is less than the minimum threshold, modifying the multi-domain combined speech recognition model specifically to the specific speech recognition domain by weighting components of the multi-domain combined speech recognition model associated with the specific speech recognition domain to have more influence in recognition of the speech from the user.
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11. A system comprising: a processor; and a computer-readable storage medium having instruction stored which, when executed by the processor, result in the processor performing operations comprising: receiving speech from a user as part of a speech dialog between the user and a speech recognition service; identifying, based on the speech, a speech pattern of the user; identifying, based on the speech pattern of the user, a plurality of speech recognition models stored in a cloud computing storage environment, each speech recognition model of the plurality of speech recognition models being from a respective speech recognition domain; combining the plurality of speech recognition models, to yield a multi-domain combined speech recognition model; identifying in the speech a specific speech recognition domain, wherein the specific speech recognition domain does not match a specific speech recognition model in the plurality of speech recognition models; receiving sample data associated with the specific speech recognition domain, wherein the sample data is independent of the speech dialog between the user and the speech recognition service; when the sample data is more than a minimum threshold, generating a new domain-specific speech recognition model for the specific speech recognition domain; and when sample data is less than the minimum threshold, modifying the multi-domain combined speech recognition model specifically to the specific speech recognition domain by weighting components of the multi-domain combined speech recognition model associated with the specific speech recognition domain to have more influence in recognition of the speech from the user. 13. The system of claim 11 , wherein the plurality of speech recognition models comprises two speech recognition models from different domains.
| 0.815245 |
8,832,556 | 15 | 19 |
15. A method comprising: configuring a distributed database with items of data, the distributed database storing information of a social networking system describing a plurality of existing users; configuring a scripting language to extract data from the social networking system, the data extraction applying access control comprising privacy settings of each user of the social networking system, the privacy settings restricting the information about the user that is accessible to other users of the social networking system; and configuring a structured query language interface configured to access database systems to receive a query requesting information from the social networking system over a network, to send the query to the scripting language, and to receive extracted data from the scripting language comprising the requested information subject to the privacy settings of users of the social networking system in response to the query adding, by the social networking system, to the distributed database a new field or category of data to the plurality of existing users, the new field or category of data representing an attribute describing each user of the plurality of existing users and storing data directly received from one or more users of the social networking system rather than data derived from one or more existing fields of data; receiving a request from an application or website maintained by a third party separate from the social networking system, the request identifying the new field or category of data; generating a response to the request, the response comprising the new field or category of data; determining a format for the response to accommodate a database of the third party; converting the response comprising the new field or category of data into the determined format; and providing the response in the determined format to the third party.
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15. A method comprising: configuring a distributed database with items of data, the distributed database storing information of a social networking system describing a plurality of existing users; configuring a scripting language to extract data from the social networking system, the data extraction applying access control comprising privacy settings of each user of the social networking system, the privacy settings restricting the information about the user that is accessible to other users of the social networking system; and configuring a structured query language interface configured to access database systems to receive a query requesting information from the social networking system over a network, to send the query to the scripting language, and to receive extracted data from the scripting language comprising the requested information subject to the privacy settings of users of the social networking system in response to the query adding, by the social networking system, to the distributed database a new field or category of data to the plurality of existing users, the new field or category of data representing an attribute describing each user of the plurality of existing users and storing data directly received from one or more users of the social networking system rather than data derived from one or more existing fields of data; receiving a request from an application or website maintained by a third party separate from the social networking system, the request identifying the new field or category of data; generating a response to the request, the response comprising the new field or category of data; determining a format for the response to accommodate a database of the third party; converting the response comprising the new field or category of data into the determined format; and providing the response in the determined format to the third party. 19. The method of claim 15 , the method further comprising: configuring the structured query language interface to send some or all of the extracted data in a format to accommodate a database maintained by a third-party developer.
| 0.524793 |
9,026,522 | 1 | 2 |
1. A computer-implemented Whols search method comprising steps of: receiving and storing domain names and corresponding owner information associated with the domain names in one or more networked databases; determining suffixes of the domain names that have at least a minimum length of characters: indexing the suffixes of the domain names determined to have the minimum length of characters and suffixes of text-searchable portions of the corresponding owner information; storing the suffixes in one or more text indexes; receiving a search request and one or more search preferences from a user; searching the one or more text indexes in response to the search request; receiving search results including at least one matched domain name; querying the one or more network databases for owner information corresponding to the at least one matched domain name; and displaying the at least one matched domain name and the corresponding owner information to the user.
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1. A computer-implemented Whols search method comprising steps of: receiving and storing domain names and corresponding owner information associated with the domain names in one or more networked databases; determining suffixes of the domain names that have at least a minimum length of characters: indexing the suffixes of the domain names determined to have the minimum length of characters and suffixes of text-searchable portions of the corresponding owner information; storing the suffixes in one or more text indexes; receiving a search request and one or more search preferences from a user; searching the one or more text indexes in response to the search request; receiving search results including at least one matched domain name; querying the one or more network databases for owner information corresponding to the at least one matched domain name; and displaying the at least one matched domain name and the corresponding owner information to the user. 2. The computer-implemented Whols search method of claim 1 , wherein the one or more networked databases and one or more text indexes store domain names and owner information for multiple top level domains, and the received search request is processed with respect to all stored top level domains.
| 0.555389 |
8,037,084 | 3 | 4 |
3. The method of claim 1 wherein the instructions to locate some of the subset of data comprise a directional reference to indicate that the position of the some of the subset of data relative to a particular signature comprises one of: 1) before the particular signature; 2) after the particular signature; or 3) both before and after the particular signature.
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3. The method of claim 1 wherein the instructions to locate some of the subset of data comprise a directional reference to indicate that the position of the some of the subset of data relative to a particular signature comprises one of: 1) before the particular signature; 2) after the particular signature; or 3) both before and after the particular signature. 4. The method of claim 3 wherein the instructions to locate some of the subset of data further comprise: at least one of: i) a start reference; or ii) an end reference, said start reference and end reference respectively indicating a starting location and ending location for the some of the subset of data relative to the signature and in accordance with the direction indicated by the directional reference.
| 0.5 |
9,239,889 | 7 | 8 |
7. An application data processing system configured for semantically aware adaptive searching and navigation of application data, the system comprising: a host computing system comprising one or more server computers each with memory and at least one processor; a data driven application executing in the memory of the host computing system; a database of unstructured data coupled to the host computing system; a plurality of different objects encapsulating data and specified according to different semantics stored in the memory of the host computing system; and, an adaptive search and navigation module executing in the memory of the host computing system, the module comprising program code enabled to associate different tags with different data of the database of unstructured data, each of the different tags corresponding to selected ones of the different semantics, to apply a filter operation to both the tags of the unstructured data and also the different objects, using filter criteria corresponding to one or more semantics of the different objects encapsulating data, to display in a user interface to the data driven application a result set from the filter operation, to receive keyword search terms in a search field of the user interface, to apply a keyword search operation both to the unstructured data and also the encapsulated data of the different obiects using the keyword search terms, to aggregate the result set from the keyword search operation with the result set from the filter operation, and to display in the user interface the aggregation.
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7. An application data processing system configured for semantically aware adaptive searching and navigation of application data, the system comprising: a host computing system comprising one or more server computers each with memory and at least one processor; a data driven application executing in the memory of the host computing system; a database of unstructured data coupled to the host computing system; a plurality of different objects encapsulating data and specified according to different semantics stored in the memory of the host computing system; and, an adaptive search and navigation module executing in the memory of the host computing system, the module comprising program code enabled to associate different tags with different data of the database of unstructured data, each of the different tags corresponding to selected ones of the different semantics, to apply a filter operation to both the tags of the unstructured data and also the different objects, using filter criteria corresponding to one or more semantics of the different objects encapsulating data, to display in a user interface to the data driven application a result set from the filter operation, to receive keyword search terms in a search field of the user interface, to apply a keyword search operation both to the unstructured data and also the encapsulated data of the different obiects using the keyword search terms, to aggregate the result set from the keyword search operation with the result set from the filter operation, and to display in the user interface the aggregation. 8. The system of claim 7 , wherein the program code is further enabled to receive keyword search terms in a search field of the user interface, to apply a keyword search operation to the unstructured data using the keyword search terms and to display in the user interface a result set from the keyword search operation.
| 0.598997 |
8,326,847 | 6 | 7 |
6. A method of finding relationships between objects in a database comprising: generating an instance graph expressing relationships between the objects in said database; receiving a query including at least two terms; rewriting, heuristically, the query into an ordered list of sub-query terms, wherein the ordered list begins with first and second search terms; executing, with a processor, the first search term in a query, wherein said executing derives a subset of said database; performing a relationship search that ranks each object in said instance graph with respect to said subset; filtering out the objects of said relationship search, wherein each filtered out object has a score below a predetermined threshold; generating a summary graph using the subset of said executing; aggregating to said summary graph two or more of said filtered out objects which are related to at least one object having a score above said predetermined threshold; and executing said second search term on said summary graph, wherein the execution outputs second subset.
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6. A method of finding relationships between objects in a database comprising: generating an instance graph expressing relationships between the objects in said database; receiving a query including at least two terms; rewriting, heuristically, the query into an ordered list of sub-query terms, wherein the ordered list begins with first and second search terms; executing, with a processor, the first search term in a query, wherein said executing derives a subset of said database; performing a relationship search that ranks each object in said instance graph with respect to said subset; filtering out the objects of said relationship search, wherein each filtered out object has a score below a predetermined threshold; generating a summary graph using the subset of said executing; aggregating to said summary graph two or more of said filtered out objects which are related to at least one object having a score above said predetermined threshold; and executing said second search term on said summary graph, wherein the execution outputs second subset. 7. The method of claim 6 wherein said received query includes a third search term and further comprising executing said third search term on the results of said second subset.
| 0.50565 |
9,279,695 | 1 | 2 |
1. A method for a navigation system, the method comprising: receiving a query text string representing a request for a geographic location from a user; obtaining candidate information data records representing stored locations from a geographic database stored on a computer readable medium, each of the candidate information data records comprising a record text string of a different geographic location; computing, by a processor, a text matching score for each of the different geographic locations, wherein the text matching score indicates a degree of match between the query text string and each of the different geographic locations; computing, by the processor, a usage pattern weight for each of the different geographic locations, wherein the usage pattern weight represents a frequency that users have previously selected a corresponding geographic location; computing, by the processor, a ranking score (s) based on a product of the text matching score (s f ) and the usage pattern weight (w(f)) for each of the different geographic locations according to s=s f *w(f); ranking the different geographic locations based on the ranking scores; and displaying the different geographic locations according to the ranking scores, wherein said usage pattern weight is determined using historic crowd sourcing or real time crowd sourcing.
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1. A method for a navigation system, the method comprising: receiving a query text string representing a request for a geographic location from a user; obtaining candidate information data records representing stored locations from a geographic database stored on a computer readable medium, each of the candidate information data records comprising a record text string of a different geographic location; computing, by a processor, a text matching score for each of the different geographic locations, wherein the text matching score indicates a degree of match between the query text string and each of the different geographic locations; computing, by the processor, a usage pattern weight for each of the different geographic locations, wherein the usage pattern weight represents a frequency that users have previously selected a corresponding geographic location; computing, by the processor, a ranking score (s) based on a product of the text matching score (s f ) and the usage pattern weight (w(f)) for each of the different geographic locations according to s=s f *w(f); ranking the different geographic locations based on the ranking scores; and displaying the different geographic locations according to the ranking scores, wherein said usage pattern weight is determined using historic crowd sourcing or real time crowd sourcing. 2. The method of claim 1 , further comprising: providing the geographic location corresponding to a highest ranking score; receiving a selection of the provided geographic location from the user; and increasing the usage pattern weight for the provided candidate information that was selected.
| 0.5 |
8,965,904 | 10 | 14 |
10. A computer implemented method for searching and ranking a list of files-of-interest, comprising: receiving an user input query comprising a plurality of keywords; for each file in the list: a—determine a number of unmatched query-keywords during searching each paragraph of the file, and if the number of unmatched query-keywords is greater than a portion of a total number of keywords in the query, set the paragraph score to zero and skip to a next paragraph, b—determine a number of unique matched query-keywords for each paragraph of the file, c—determine a number of matched keywords occurred in each paragraph of the file, d—determine a plurality of distances between matched keywords within each paragraph, e—determine a number of distances less than a threshold distance within each paragraph, f—determine a plurality of paragraph scores, wherein each paragraph score is calculated based on said number of matched keywords, said number of unique matched query-keywords, a distance from said plurality of distances, and said number of distances less than said threshold distance, g—determine an overall score based on at least two of said plurality of paragraph scores, wherein each overall score comprises a plurality of scores; sorting and ranking said files based on the overall scores of said files; and presenting results of said ranking to the user, wherein said sorting and ranking is based on both priority levels and score values of said plurality of scores, said priority levels of said plurality of scores are initially set according to a default setting, in response to the score values of at least two current compared scores are equal, the score values of at least two respective scores with lower priority are used for ranking.
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10. A computer implemented method for searching and ranking a list of files-of-interest, comprising: receiving an user input query comprising a plurality of keywords; for each file in the list: a—determine a number of unmatched query-keywords during searching each paragraph of the file, and if the number of unmatched query-keywords is greater than a portion of a total number of keywords in the query, set the paragraph score to zero and skip to a next paragraph, b—determine a number of unique matched query-keywords for each paragraph of the file, c—determine a number of matched keywords occurred in each paragraph of the file, d—determine a plurality of distances between matched keywords within each paragraph, e—determine a number of distances less than a threshold distance within each paragraph, f—determine a plurality of paragraph scores, wherein each paragraph score is calculated based on said number of matched keywords, said number of unique matched query-keywords, a distance from said plurality of distances, and said number of distances less than said threshold distance, g—determine an overall score based on at least two of said plurality of paragraph scores, wherein each overall score comprises a plurality of scores; sorting and ranking said files based on the overall scores of said files; and presenting results of said ranking to the user, wherein said sorting and ranking is based on both priority levels and score values of said plurality of scores, said priority levels of said plurality of scores are initially set according to a default setting, in response to the score values of at least two current compared scores are equal, the score values of at least two respective scores with lower priority are used for ranking. 14. The method according to claim 10 , further comprising: eliminating a file if at least one of said plurality of scores of the file does not meet a predetermined criteria.
| 0.843013 |
7,747,495 | 1 | 11 |
1. A method of doing business by processing a group of documents comprising the steps of: (1) performing optical character recognition from said discrete documents using said device to generate one or more sets of text-based information; (2) classifying at least some of said discrete documents using said sets of text-based information, wherein multiple classification engines are employed and said classifying is based on a consensus of said classification engines; (3) classifying at least some of the discrete documents using Image Based Classification; (4) verifying any of said remaining discrete documents that are not classified in said steps of classifying by employing a Location Diagram with said remaining discrete documents or a portion thereof; (5) collating said at least two of said discrete documents; (6) versioning and sequencing at least two of said discrete documents; (7) locating said fields containing data in said at least two of said discrete documents; (8) extracting data from said fields of said at least two discrete documents to generate extracted data; (9) scrubbing values from said extracted data to generate values therefrom; (10) forming Knowledge Objects; (11) storing said values in a data storage device; (12) forming Business Objects; (13) displaying at least some of said values to a user.
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1. A method of doing business by processing a group of documents comprising the steps of: (1) performing optical character recognition from said discrete documents using said device to generate one or more sets of text-based information; (2) classifying at least some of said discrete documents using said sets of text-based information, wherein multiple classification engines are employed and said classifying is based on a consensus of said classification engines; (3) classifying at least some of the discrete documents using Image Based Classification; (4) verifying any of said remaining discrete documents that are not classified in said steps of classifying by employing a Location Diagram with said remaining discrete documents or a portion thereof; (5) collating said at least two of said discrete documents; (6) versioning and sequencing at least two of said discrete documents; (7) locating said fields containing data in said at least two of said discrete documents; (8) extracting data from said fields of said at least two discrete documents to generate extracted data; (9) scrubbing values from said extracted data to generate values therefrom; (10) forming Knowledge Objects; (11) storing said values in a data storage device; (12) forming Business Objects; (13) displaying at least some of said values to a user. 11. The method of claim 1 , wherein said step of outputting is performed by, or with the assistance of, a computer.
| 0.659763 |
9,767,388 | 1 | 9 |
1. A method comprising: receiving, at a processor, a set of uncertain characters obtained as a result of a recognition process of a text image, the set of uncertain characters including an image of an uncertain character, a hypothesis about the uncertain character, and a confidence level associated with the hypothesis; causing, by the processor, a display device to present to a user the image of the uncertain character from the set of uncertain characters over a text readout; receiving, at the processor from a user input, marking data for the uncertain character; and adjusting, using the received marking data, the confidence level associated with the hypothesis about the uncertain character for obtaining a confirmed hypothesis linked to the uncertain character.
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1. A method comprising: receiving, at a processor, a set of uncertain characters obtained as a result of a recognition process of a text image, the set of uncertain characters including an image of an uncertain character, a hypothesis about the uncertain character, and a confidence level associated with the hypothesis; causing, by the processor, a display device to present to a user the image of the uncertain character from the set of uncertain characters over a text readout; receiving, at the processor from a user input, marking data for the uncertain character; and adjusting, using the received marking data, the confidence level associated with the hypothesis about the uncertain character for obtaining a confirmed hypothesis linked to the uncertain character. 9. The method of claim 1 , wherein the image of the uncertain character is inserted in place of a hypothesis character image within a word in the text readout, and wherein the marking data is indicative of whether the word as a whole was marked.
| 0.876012 |
9,495,413 | 7 | 8 |
7. The method of claim 1 , wherein generating one or more input fields comprises: identifying one or more parameters associated with the selected database object; determining a respective type associated with each of the one or more parameters; and iteratively generating one or more respective input fields based on the determined respective types.
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7. The method of claim 1 , wherein generating one or more input fields comprises: identifying one or more parameters associated with the selected database object; determining a respective type associated with each of the one or more parameters; and iteratively generating one or more respective input fields based on the determined respective types. 8. The method of claim 7 , wherein generating one or more respective input fields based on the determined respective types comprises: identifying at least one parameter type as a parameter type to receive particular processing; accessing one or more rules for processing the identified at least one parameter type; and processing the identified at least one parameter type utilizing the accessed one or more rules.
| 0.5 |
6,112,304 | 26 | 57 |
26. A computer system implementing an ecosystem computing architecture, the computer system comprising: an operational environment for distributed computing processes here termed denizens, each denizen including a configuration portion an origin portion, and an executable portion, each denizen performing at least one step on itself, the operational environment including at least two locations, each location providing access to a processor for executing instructions and providing a memory accessible to the processor for storing instructions; a transport means for denizens to travel between the locations; and at least one denizen that is a user denizen which receives instructions, evaluates different locations in the operational environment in view of the received instructions, selects a location based on that evaluation, moves itself to the selected location, and executes at least a portion of the received instructions at the selected location.
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26. A computer system implementing an ecosystem computing architecture, the computer system comprising: an operational environment for distributed computing processes here termed denizens, each denizen including a configuration portion an origin portion, and an executable portion, each denizen performing at least one step on itself, the operational environment including at least two locations, each location providing access to a processor for executing instructions and providing a memory accessible to the processor for storing instructions; a transport means for denizens to travel between the locations; and at least one denizen that is a user denizen which receives instructions, evaluates different locations in the operational environment in view of the received instructions, selects a location based on that evaluation, moves itself to the selected location, and executes at least a portion of the received instructions at the selected location. 57. The computer system of claim 26, further comprising means for spawning at least one thread in response to a query.
| 0.689474 |
9,214,043 | 1 | 10 |
1. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: based on a received free-space user gesture associated with a real-world geographic location where the gesture was performed and a gesture direction representing the direction in which the user gesture was made, automatically provide for the making of an annotation to a map comprising three-dimensional models of geographic elements, the three-dimensional models including surfaces that correspond to real-world surfaces of geographical elements represented in the model, wherein analysis of the map of three-dimensional models using the real-world geographic location and the gesture direction provides for identification of an annotation point comprising a particular surface of the surfaces of the three-dimensional models, the annotation being based on said user gesture and positioned at the annotation point on the particular surface of the three-dimensional model of the map to be rendered onto said surface of the three-dimensional model and wherein if a particular surface cannot be identified, the annotation is positioned at a location in the map corresponding to the real-world geographic location.
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1. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: based on a received free-space user gesture associated with a real-world geographic location where the gesture was performed and a gesture direction representing the direction in which the user gesture was made, automatically provide for the making of an annotation to a map comprising three-dimensional models of geographic elements, the three-dimensional models including surfaces that correspond to real-world surfaces of geographical elements represented in the model, wherein analysis of the map of three-dimensional models using the real-world geographic location and the gesture direction provides for identification of an annotation point comprising a particular surface of the surfaces of the three-dimensional models, the annotation being based on said user gesture and positioned at the annotation point on the particular surface of the three-dimensional model of the map to be rendered onto said surface of the three-dimensional model and wherein if a particular surface cannot be identified, the annotation is positioned at a location in the map corresponding to the real-world geographic location. 10. An apparatus according to claim 1 , wherein the apparatus provides for the association of particular user-selected or user-provided gestures with pre-prepared notes or graphic elements.
| 0.822034 |
8,453,128 | 12 | 16 |
12. A system for implementing a just-in-time complier, comprising: means for obtaining a plurality of high-level code templates in a high-level programming language, wherein the high-level programming language is designed for compilation to an intermediate language capable of execution by a virtual machine, and wherein each high-level code template selected from the plurality of high-level code templates represents an instruction in the intermediate language; means for compiling the plurality of high-level code templates to native code to obtain a plurality of optimized native code templates, wherein compiling the plurality of high-level code templates is performed, prior to runtime, using an optimizing static compiler designed for runtime use with the virtual machine; means for marking a constant in an optimized native code template selected from the plurality of optimized native code templates with an annotation, wherein the annotation indicates that the constant requires modification by the just-in-time compiler at runtime; and means for implementing the just-in-time compiler using the plurality of optimized native code templates, wherein the just-in-time compiler is configured to substitute a copy of an optimized native code template selected from the plurality of optimized native code templates when a corresponding instruction in the intermediate language is encountered at runtime.
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12. A system for implementing a just-in-time complier, comprising: means for obtaining a plurality of high-level code templates in a high-level programming language, wherein the high-level programming language is designed for compilation to an intermediate language capable of execution by a virtual machine, and wherein each high-level code template selected from the plurality of high-level code templates represents an instruction in the intermediate language; means for compiling the plurality of high-level code templates to native code to obtain a plurality of optimized native code templates, wherein compiling the plurality of high-level code templates is performed, prior to runtime, using an optimizing static compiler designed for runtime use with the virtual machine; means for marking a constant in an optimized native code template selected from the plurality of optimized native code templates with an annotation, wherein the annotation indicates that the constant requires modification by the just-in-time compiler at runtime; and means for implementing the just-in-time compiler using the plurality of optimized native code templates, wherein the just-in-time compiler is configured to substitute a copy of an optimized native code template selected from the plurality of optimized native code templates when a corresponding instruction in the intermediate language is encountered at runtime. 16. The system of claim 12 , wherein the constant is one selected from the group consisting of an offset to a field of an object, an index into a virtual method dispatch table, a literal constant, a reference to a runtime representations of a class, and a reference to a statically linked method.
| 0.692946 |
8,190,647 | 4 | 5 |
4. The computer-implemented method of claim 1 , wherein determining the weighted impurity reduction score comprises: determining a weight value for each of the at least one of the predetermined set of attributes by applying a weight function to the complexity score of each of the at least one of the predetermined set of attributes, the weight value for an attribute measuring a significance of the complexity score of the attribute for the current set, wherein the weighted impurity reduction score for the attribute is determined based on the weight value of the attribute.
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4. The computer-implemented method of claim 1 , wherein determining the weighted impurity reduction score comprises: determining a weight value for each of the at least one of the predetermined set of attributes by applying a weight function to the complexity score of each of the at least one of the predetermined set of attributes, the weight value for an attribute measuring a significance of the complexity score of the attribute for the current set, wherein the weighted impurity reduction score for the attribute is determined based on the weight value of the attribute. 5. The computer-implemented method of claim 4 , wherein the weight function takes into consideration a size of the current set and a depth of a node for the current set in the decision tree to generate the weight value.
| 0.5 |
8,738,358 | 22 | 26 |
22. A second social media server (SM server) comprising: an input/output interface receiving from a first SM server a request for information related to a language used by the second SM server; a processor operationally connected to the input/output interface; an instructions repository storing instructions that when executed by the processor cause the later to determine the language used by the second SM server, and to return via the input/output interface to the first SM server the language used by the second SM server.
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22. A second social media server (SM server) comprising: an input/output interface receiving from a first SM server a request for information related to a language used by the second SM server; a processor operationally connected to the input/output interface; an instructions repository storing instructions that when executed by the processor cause the later to determine the language used by the second SM server, and to return via the input/output interface to the first SM server the language used by the second SM server. 26. The SM server of claim 22 , wherein step c. comprises returning from the second SM server to the first SM server a weight coefficient value representative of a usage of a language in the second SM server.
| 0.5 |
8,321,517 | 10 | 11 |
10. A system for processing emails, comprising: one or more processors and one or more non-transitory computer readable mediums storing executable program instructions comprising: program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive a correction request including an identifier of an original email and an incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to the correction request, create a correction record including the identifier of the original email and the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving relevant emails of the original email, determine whether recipients of the relevant emails include the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that a sender of the correction request is not the incorrect recipient, sending the correction request to the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive from the incorrect recipient acknowledgment to the correction request; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving from the incorrect recipient the acknowledgment to the correction request, determining the correction record to be valid; and program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that recipients of the relevant emails include the incorrect recipient and in response to determining the correction record to be valid, process the relevant emails based on the correction record.
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10. A system for processing emails, comprising: one or more processors and one or more non-transitory computer readable mediums storing executable program instructions comprising: program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive a correction request including an identifier of an original email and an incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to the correction request, create a correction record including the identifier of the original email and the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving relevant emails of the original email, determine whether recipients of the relevant emails include the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that a sender of the correction request is not the incorrect recipient, sending the correction request to the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive from the incorrect recipient acknowledgment to the correction request; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving from the incorrect recipient the acknowledgment to the correction request, determining the correction record to be valid; and program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that recipients of the relevant emails include the incorrect recipient and in response to determining the correction record to be valid, process the relevant emails based on the correction record. 11. The system according to claim 10 , wherein, the identifier of the original email is an email thread identifier of the original email, and wherein the relevant emails of the original email and the original email belong to a same email thread.
| 0.785088 |
10,097,833 | 15 | 16 |
15. A computer-implemented method of entropy decoding for video coding comprising: receiving entropy coded image data associated with a syntax having a sequence of symbols to be entropy decoded; and receiving updated probabilities for performing the entropy decoding and formed by: updating a previous probability from a previous frame relative to a current frame being entropy encoded that a symbol will occur in one of the sequences comprising: setting a search range among a set of possible update probabilities comprising: setting a first candidate probability as one end of the search range by using a count of a syntax counter and without regard to bit-cost to update the previous probability, and; setting another end of the search range as the previous probability; selecting one of the candidate probabilities on a look-up table and within the search range to update the previous probability for coding of the symbol, and selecting based on, at least in part, the bit-cost associated with updating the previous probability with at least one of the candidate probabilities; and updating the previous probability by using the selected candidate probability.
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15. A computer-implemented method of entropy decoding for video coding comprising: receiving entropy coded image data associated with a syntax having a sequence of symbols to be entropy decoded; and receiving updated probabilities for performing the entropy decoding and formed by: updating a previous probability from a previous frame relative to a current frame being entropy encoded that a symbol will occur in one of the sequences comprising: setting a search range among a set of possible update probabilities comprising: setting a first candidate probability as one end of the search range by using a count of a syntax counter and without regard to bit-cost to update the previous probability, and; setting another end of the search range as the previous probability; selecting one of the candidate probabilities on a look-up table and within the search range to update the previous probability for coding of the symbol, and selecting based on, at least in part, the bit-cost associated with updating the previous probability with at least one of the candidate probabilities; and updating the previous probability by using the selected candidate probability. 16. The method of claim 15 wherein the search range is determined by using a syntax counter that counts the number of 0s and number of 1s used to code a single bit of a syntax after the syntax has been binarized; the updated probabilities formed by generating the look-up table by associating one or more potential candidate probabilities with each update probability value of a plurality of the update probability values, wherein the update probability values form an index for the look-up table; wherein the search range is set by associating the previous probability and the first candidate probability with respective update probability values indexing the look-up table; the updated probabilities formed by: generating the look up table by establishing a range of update probabilities as an index of the look-up table by using initial previous probabilities and corresponding initial first candidate probabilities; generating the look-up table by selecting the candidate probabilities for each update probability indexing the look-up table by selecting the probabilities from an initial range of probabilities for placement on the look-up table, wherein the selected candidate probabilities assigned to an update probability (1) each have different probability update costs relative to each other, and (2) have a probability value closest to the update candidate value that is an initial first candidate probability; limiting the searching to a maximum of three candidate probabilities in addition to the first candidate probability and for each single bit of a syntax; selecting candidate probabilities based on, at least in part, comparing a new probability based value to a previous probability based value; selecting candidate probabilities, at least in part, depending on the results of one of: (1) determining the difference between the new probability based value and a candidate probability from the look up table selected by using the new probability based value as an index number to look up the candidate probability, and (2) determining the difference between (a) a change value based on, at least in part, the difference between the new probability and the previous probability, and (b) a candidate probability from the look up table selected by using the change value as an index number to look up the candidate probability; adjusting an initial value of a probability candidate from the look up table depending on a comparison between the initial value and the previous probability based value, and setting the value of the probability candidate by using the difference in a calculation; and performing an early exit comprising using the first candidate probability for updating when a second probability candidate being the first probability candidate selected from the look-up table has a bit-cost larger than or equal to the bit-cost of the first probability candidate; wherein the bit-cost comprises the bit cost to perform the update or the bit-cost to indicate an update is to be performed or both, and in the bitstream.
| 0.5 |
8,862,456 | 11 | 18 |
11. A system to translate displayed user-interface text of a computer application, comprising: an interception module configured to intercept a command to display user-interface text in a first language, the command comprising the user-interface text to display in the first language; an extraction module configured to extract user-interface text to translate from the command; an interface to a translation mechanism, wherein the interface is configured to transmit extracted user-interface text to the translation mechanism, and to receive translated user-interface text from the translation mechanism; and an output module configured to display the translated user-interface text in the second language.
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11. A system to translate displayed user-interface text of a computer application, comprising: an interception module configured to intercept a command to display user-interface text in a first language, the command comprising the user-interface text to display in the first language; an extraction module configured to extract user-interface text to translate from the command; an interface to a translation mechanism, wherein the interface is configured to transmit extracted user-interface text to the translation mechanism, and to receive translated user-interface text from the translation mechanism; and an output module configured to display the translated user-interface text in the second language. 18. The system of claim 11 , wherein the translation mechanism is configured to use a value derived from the user-interface text to translate.
| 0.755172 |
8,676,913 | 29 | 30 |
29. The method of claim 20 , further comprising: receiving data defining an active tag and a first argument for the active tag; receiving data identifying the active tag to be associated with the second discussion data structure; associating the active tag data with the second discussion data structure; and including the active tag data in the first visual feed data for display.
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29. The method of claim 20 , further comprising: receiving data defining an active tag and a first argument for the active tag; receiving data identifying the active tag to be associated with the second discussion data structure; associating the active tag data with the second discussion data structure; and including the active tag data in the first visual feed data for display. 30. The method of claim 29 , further comprising: displaying on a visual display and in association with the first sub-discussion topic an active button or active text representative of the active tag; receiving an indication that the active button or active text has been selected; and performing, responsive to receiving the indication, a functional operation associated with the active tag.
| 0.5 |
9,858,263 | 2 | 3 |
2. The method of claim 1 , further comprising: parsing the predicting canonical form to generate a logical form; and generating a query based on the logical form.
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2. The method of claim 1 , further comprising: parsing the predicting canonical form to generate a logical form; and generating a query based on the logical form. 3. The method of claim 2 , further comprising: querying a knowledge base with the query; and retrieving a response to the query from the knowledge base, the output information being based on the response.
| 0.5 |
9,241,101 | 1 | 21 |
1. A portable electronic device comprising: a display; user controls configured to enable a user to select between at least an up input, a down input, a left input, a right input, and a confirmation input; a storage memory; a data processing system; and a program memory communicatively connected to the data processing system and configured to store instructions configured to cause the data processing system to provide a user-specified input string, wherein the display is configured to display a string input interface wherein the string input interface includes: a string entry section for displaying the user-specified input string; and at least two independently scrollable character selection sections, the at least two independently scrollable character selection sections separate from the string entry section, wherein each independently scrollable character selection section enables a user to select from a corresponding predefined set of characters, wherein only a subset of the corresponding predefined set of characters are displayed in each of the at least two independently scrollable character selection sections at a particular time, wherein each of the at least two independently scrollable character selection sections enables scrolling between a plurality of characters within a respective independently scrollable character selection section; wherein the program memory includes instructions to accept user input provided using the user controls to sequentially select characters to specify the user-specified input string, wherein the up input and the down input are used to select one of the at least two independently scrollable character selection sections, the left input and the right input are used to scroll through the predefined set of characters in the selected independently scrollable character selection section to select a particular character, and the confirmation input is used to add the selected particular character to the input string displayed in the string entry section; and wherein the storage memory is configured to store the input string.
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1. A portable electronic device comprising: a display; user controls configured to enable a user to select between at least an up input, a down input, a left input, a right input, and a confirmation input; a storage memory; a data processing system; and a program memory communicatively connected to the data processing system and configured to store instructions configured to cause the data processing system to provide a user-specified input string, wherein the display is configured to display a string input interface wherein the string input interface includes: a string entry section for displaying the user-specified input string; and at least two independently scrollable character selection sections, the at least two independently scrollable character selection sections separate from the string entry section, wherein each independently scrollable character selection section enables a user to select from a corresponding predefined set of characters, wherein only a subset of the corresponding predefined set of characters are displayed in each of the at least two independently scrollable character selection sections at a particular time, wherein each of the at least two independently scrollable character selection sections enables scrolling between a plurality of characters within a respective independently scrollable character selection section; wherein the program memory includes instructions to accept user input provided using the user controls to sequentially select characters to specify the user-specified input string, wherein the up input and the down input are used to select one of the at least two independently scrollable character selection sections, the left input and the right input are used to scroll through the predefined set of characters in the selected independently scrollable character selection section to select a particular character, and the confirmation input is used to add the selected particular character to the input string displayed in the string entry section; and wherein the storage memory is configured to store the input string. 21. The portable electronic device of claim 1 , wherein the string entry section and the at least two independently scrollable character selection sections are arranged in a non-overlapping arrangement such that none of the string entry section and the at least two independently scrollable character selection sections overlap another of the string entry section and the at least two independently scrollable character selection sections.
| 0.5 |
9,507,774 | 1 | 8 |
1. A speech translation system comprising: a first terminal device comprising a first speech input for inputting a first speech of a first language spoken by a first user, and converting the first speech to a first speech signal; a second terminal device comprising a second speech input for inputting a second speech of a second language spoken by a second user, and converting the second speech to a second speech signal; a speech recognition device that receives the first speech signal and the second speech signal, recognizes the first speech signal to a first recognized text, and recognizes the second speech signal to a second recognized text; a machine translation device that receives the first recognized text and the second recognized text, translates the first recognized text to a first translated text of the second language, and translates the second recognized text to a second translated text of the first language; a control device; wherein the first terminal device receives (a) a first text set of the first language being the first recognized text and the second translated text, and (b) a second text set of the second language being the second recognized text and the first translated text, and comprises a first display unit that displays the first text set and the second text set; and the second terminal device receives at least one text of the second text set, and comprises a second display unit that displays the at least one text of the second text set; a third terminal device comprising a third speech input for inputting a third speech of a third language spoken by a third user, and converting the third speech to a third speech signal; the speech recognition device receives the third speech signal, and recognizes the third speech signal to a third recognized text; the machine translation device receives the third recognized text and the first recognized text, further comprises a third machine translation unit that translates the third recognized text to the third translated text of the first language, and translates the first recognized text to the fourth translated text of the third language; the first display unit displays (a) at least one text set of the second text set and a third text set of the third language being the third recognized text and the fourth translated text, and (b) the fourth text set of the first language being the first text set and the third translated text; and the third terminal device further comprises the third display unit that displays at least one text of the third text set.
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1. A speech translation system comprising: a first terminal device comprising a first speech input for inputting a first speech of a first language spoken by a first user, and converting the first speech to a first speech signal; a second terminal device comprising a second speech input for inputting a second speech of a second language spoken by a second user, and converting the second speech to a second speech signal; a speech recognition device that receives the first speech signal and the second speech signal, recognizes the first speech signal to a first recognized text, and recognizes the second speech signal to a second recognized text; a machine translation device that receives the first recognized text and the second recognized text, translates the first recognized text to a first translated text of the second language, and translates the second recognized text to a second translated text of the first language; a control device; wherein the first terminal device receives (a) a first text set of the first language being the first recognized text and the second translated text, and (b) a second text set of the second language being the second recognized text and the first translated text, and comprises a first display unit that displays the first text set and the second text set; and the second terminal device receives at least one text of the second text set, and comprises a second display unit that displays the at least one text of the second text set; a third terminal device comprising a third speech input for inputting a third speech of a third language spoken by a third user, and converting the third speech to a third speech signal; the speech recognition device receives the third speech signal, and recognizes the third speech signal to a third recognized text; the machine translation device receives the third recognized text and the first recognized text, further comprises a third machine translation unit that translates the third recognized text to the third translated text of the first language, and translates the first recognized text to the fourth translated text of the third language; the first display unit displays (a) at least one text set of the second text set and a third text set of the third language being the third recognized text and the fourth translated text, and (b) the fourth text set of the first language being the first text set and the third translated text; and the third terminal device further comprises the third display unit that displays at least one text of the third text set. 8. The system according to claim 1 , wherein the speech recognition device outputs the recognized text and a recognition likelihood representing confidence of the speech recognition process; the control device further comprises a second recognition display decision unit that decide whether the second recognition text is displayed on the second display unit, based on the recognition likelihood.
| 0.640653 |
9,811,683 | 1 | 2 |
1. A computer system comprising: one or more processors; one or more computer readable memories; and one or more non-transitory computer readable storage mediums, wherein program instructions are stored on at least one of the one or more non-transitory storage mediums for execution by at least one of the one or more processors via at least one of the one or more computer readable memories to perform a method comprising: associating a first non-contextual data object with a first context object to define a first synthetic context-based object, wherein the first non-contextual data object describes multiple types of persons, wherein the first context object provides a context that identifies a specific type of person from the multiple types of persons, and wherein the first context object further describes a location of a computer that is being used by a requester of data as being a public Wi-Fi hot spot that provides the computer with access to a network; associating the first synthetic context-based object with at least one specific data store in a data structure; receiving a string of binary data that describes a request, from the requester, for data from said at least one specific data store in the data structure; determining the context according to the physical location of the computer being used, by the requester, to send the request to a security module; generating a new synthetic context-based object for the requester; determining whether the new synthetic context-based object matches the first synthetic context-based object; in response to determining that the new synthetic context-based object matches the first synthetic context-based object, locating, via the first synthetic context-based object, said at least one specific data store; providing the requester access to said at least one specific data store; constructing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving the request for data from at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; receiving a time window for receiving the data from said at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library, wherein the time window describes an amount of time that the requester of data is willing to wait for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; determining a security level of the requester based on the time window received from the requester, wherein a first time window that the requester to willing to wait for the at least one data store is longer than a second time window that the requester is willing to wait for the at least one data store, and wherein the first time window is indicative of a higher security level for the requester than the second time window; matching, based on the time window for the requester, the security level of the requester to data from said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, data from said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library and that matches the security level of the requester.
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1. A computer system comprising: one or more processors; one or more computer readable memories; and one or more non-transitory computer readable storage mediums, wherein program instructions are stored on at least one of the one or more non-transitory storage mediums for execution by at least one of the one or more processors via at least one of the one or more computer readable memories to perform a method comprising: associating a first non-contextual data object with a first context object to define a first synthetic context-based object, wherein the first non-contextual data object describes multiple types of persons, wherein the first context object provides a context that identifies a specific type of person from the multiple types of persons, and wherein the first context object further describes a location of a computer that is being used by a requester of data as being a public Wi-Fi hot spot that provides the computer with access to a network; associating the first synthetic context-based object with at least one specific data store in a data structure; receiving a string of binary data that describes a request, from the requester, for data from said at least one specific data store in the data structure; determining the context according to the physical location of the computer being used, by the requester, to send the request to a security module; generating a new synthetic context-based object for the requester; determining whether the new synthetic context-based object matches the first synthetic context-based object; in response to determining that the new synthetic context-based object matches the first synthetic context-based object, locating, via the first synthetic context-based object, said at least one specific data store; providing the requester access to said at least one specific data store; constructing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving the request for data from at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; receiving a time window for receiving the data from said at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library, wherein the time window describes an amount of time that the requester of data is willing to wait for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; determining a security level of the requester based on the time window received from the requester, wherein a first time window that the requester to willing to wait for the at least one data store is longer than a second time window that the requester is willing to wait for the at least one data store, and wherein the first time window is indicative of a higher security level for the requester than the second time window; matching, based on the time window for the requester, the security level of the requester to data from said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, data from said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library and that matches the security level of the requester. 2. The computer system of claim 1 , wherein the method further comprises: blocking the requester from accessing data stores other than said at least one specific data store in the data structure.
| 0.883234 |
8,386,450 | 1 | 2 |
1. A method of optimizing execution of a query that accesses data stored on a data store connected to a computer, comprising: using statistics on one or more expressions of one or more pre-defined queries to determine an optimal query execution plan for the query; and executing the optimal query execution plan for the query in order to access the data stored on the data store connected to a computer and then output the accessed data.
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1. A method of optimizing execution of a query that accesses data stored on a data store connected to a computer, comprising: using statistics on one or more expressions of one or more pre-defined queries to determine an optimal query execution plan for the query; and executing the optimal query execution plan for the query in order to access the data stored on the data store connected to a computer and then output the accessed data. 2. The method of claim 1 , wherein each of the pre-defined queries is associated with an automatic summary table, a materialized view or a view.
| 0.785075 |
9,690,850 | 14 | 20 |
14. An apparatus comprising: a memory unit; and a processor coupled to the memory unit and configured to execute a plurality of instructions which are configured to when executed cause the apparatus to: retrieve recipe text information from a client device in communication with the apparatus, the recipe text information comprising at least a plurality of words relating to preparation of a food or beverage; analyze the text information to determine one of a plurality of keyword categories for individual ones of the plurality of words in the text information, the keyword categories being determined based on a presence of the individual ones of the plurality of words within a database of known words for each of three available keyword categories; extract nutrition information associated with at least the individual ones of the words identified within the keyword category relating to known ingredients; organize the extracted nutrition information and the plurality of words into sections related to the keyword categories; and provide the organized extracted nutrition information and the plurality of words to the client device for nutrition logging thereat.
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14. An apparatus comprising: a memory unit; and a processor coupled to the memory unit and configured to execute a plurality of instructions which are configured to when executed cause the apparatus to: retrieve recipe text information from a client device in communication with the apparatus, the recipe text information comprising at least a plurality of words relating to preparation of a food or beverage; analyze the text information to determine one of a plurality of keyword categories for individual ones of the plurality of words in the text information, the keyword categories being determined based on a presence of the individual ones of the plurality of words within a database of known words for each of three available keyword categories; extract nutrition information associated with at least the individual ones of the words identified within the keyword category relating to known ingredients; organize the extracted nutrition information and the plurality of words into sections related to the keyword categories; and provide the organized extracted nutrition information and the plurality of words to the client device for nutrition logging thereat. 20. The apparatus of claim 14 , wherein the plurality of instructions are further configured when executed cause the apparatus to determine a language of the plurality of text based at least in part on a geographic location of the client device; and analyze the individual words comprising the plurality of text relating to the recipe to determine whether each may be found within one of three keyword databases of known words for the determined language.
| 0.604348 |
9,336,299 | 9 | 10 |
9. The computing device of claim 8 , wherein the first seed phrase is the word “orange” and the first seed probabilities include an individual first seed probability that the word “orange” means a type of fruit and another individual first seed probability that the word “orange” means a particular color.
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9. The computing device of claim 8 , wherein the first seed phrase is the word “orange” and the first seed probabilities include an individual first seed probability that the word “orange” means a type of fruit and another individual first seed probability that the word “orange” means a particular color. 10. The computing device of claim 9 , wherein the word “orange” is assigned a relatively higher probability of meaning the type of fruit than of meaning the particular color.
| 0.5 |
5,438,630 | 12 | 16 |
12. A processor-based method Of determining whether a keyword made up of characters is present in a bitmap input image containing words, the words being considered to extend horizontally, the method comprising the steps of: providing a set of previously trained single-character HMMs, each single-character HMM having a number of possible contexts, depending on whether the character has an ascender or a descender; concatenating those single-character HMMs that correspond to the characters in the keyword so as to provide a keyword HMM, the context of a given single-character HMM used to create the keyword HMM being determined on the basis of whether the keyword contains characters having ascenders or descenders; providing a non-keyword HMM; constructing a network that includes a first path passing through the keyword HMM and a second path passing through the non-keyword HMM but not passing through the keyword HMM; locating a portion of the input image potentially containing a word; providing an array of pixel values, referred to as a potential keyword, representing the portion of the input image; generating a set of features based on the potential keyword, the set of features providing shape information regarding the word potentially contained in the portion of the input image; the set of features being generated at a plurality of uniformly spaced horizontal locations, thereby avoiding segmentation of the potential keyword in a manner that depends on values of the pixels in the potential keyword; applying the set of features to the HMM network; finding a path through the network that maximizes the probability of the set of features as applied to the network; and determining whether the path that maximizes the probability passes through the keyword HMM so as to provide an indication whether the potential keyword is the keyword.
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12. A processor-based method Of determining whether a keyword made up of characters is present in a bitmap input image containing words, the words being considered to extend horizontally, the method comprising the steps of: providing a set of previously trained single-character HMMs, each single-character HMM having a number of possible contexts, depending on whether the character has an ascender or a descender; concatenating those single-character HMMs that correspond to the characters in the keyword so as to provide a keyword HMM, the context of a given single-character HMM used to create the keyword HMM being determined on the basis of whether the keyword contains characters having ascenders or descenders; providing a non-keyword HMM; constructing a network that includes a first path passing through the keyword HMM and a second path passing through the non-keyword HMM but not passing through the keyword HMM; locating a portion of the input image potentially containing a word; providing an array of pixel values, referred to as a potential keyword, representing the portion of the input image; generating a set of features based on the potential keyword, the set of features providing shape information regarding the word potentially contained in the portion of the input image; the set of features being generated at a plurality of uniformly spaced horizontal locations, thereby avoiding segmentation of the potential keyword in a manner that depends on values of the pixels in the potential keyword; applying the set of features to the HMM network; finding a path through the network that maximizes the probability of the set of features as applied to the network; and determining whether the path that maximizes the probability passes through the keyword HMM so as to provide an indication whether the potential keyword is the keyword. 16. The method of claim 12 wherein the set of features for the potential keyword includes a plurality of multi-parameter feature vectors determined at respective ones of the plurality of uniformly spaced horizontal locations in the potential keyword, a given feature vector for a given horizontal location representing pixel values at the given horizontal location.
| 0.709857 |
9,218,803 | 11 | 12 |
11. The system of claim 9 , wherein the primary speech database has been further modified by identifying boundaries of the primary speech segment.
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11. The system of claim 9 , wherein the primary speech database has been further modified by identifying boundaries of the primary speech segment. 12. The system of claim 11 , wherein phone boundaries of the primary speech segment are identified using a zero-crossing calculation.
| 0.5 |
8,674,855 | 28 | 29 |
28. The system of claim 26 , wherein the controller is configured to initiate the action by: disabling the imaging device, generating a visual signal, generating an audible signal, writing an entry into a log, sending a message to a remote system, or generating an automated invoice for royalties.
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28. The system of claim 26 , wherein the controller is configured to initiate the action by: disabling the imaging device, generating a visual signal, generating an audible signal, writing an entry into a log, sending a message to a remote system, or generating an automated invoice for royalties. 29. The system of claim 28 , wherein the remote system comprises: a memory device configured to store the target code.
| 0.63125 |
8,254,698 | 1 | 2 |
1. A method for document-to-template matching for data-leak prevention (DLP), the method comprising the steps of: (a) providing a document as a stream of characters; (b) splitting said stream into a plurality of non-overlapping serialized data lines, with each said serialized data line including at least two side characters; (c) calculating a hash value for each said serialized data line; (d) checking for each said hash value in a hash map of a template set; (e) determining a similarity match to a particular template based on a predefined threshold of template hash values, of said template set, being found in said stream; and (f) based on said similarity match, executing a DLP security policy for said document.
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1. A method for document-to-template matching for data-leak prevention (DLP), the method comprising the steps of: (a) providing a document as a stream of characters; (b) splitting said stream into a plurality of non-overlapping serialized data lines, with each said serialized data line including at least two side characters; (c) calculating a hash value for each said serialized data line; (d) checking for each said hash value in a hash map of a template set; (e) determining a similarity match to a particular template based on a predefined threshold of template hash values, of said template set, being found in said stream; and (f) based on said similarity match, executing a DLP security policy for said document. 2. The method of claim 1 , wherein said DLP security policy includes at least one of the enforcement actions selected from the group consisting of: quarantining said document, blocking said document from being transmitted, and releasing said document for transmission only upon administrator approval.
| 0.5 |
6,058,166 | 17 | 18 |
17. The system recited in claim 13 wherein at least one of the prompt definitions in one of the subsets other than the base subset comprises a modified form of a corresponding prompt definition in the base subset.
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17. The system recited in claim 13 wherein at least one of the prompt definitions in one of the subsets other than the base subset comprises a modified form of a corresponding prompt definition in the base subset. 18. The system recited in claim 17 wherein the prompt definitions in the base subset and in each of the other subsets has an identification code (ID) associated therewith, and wherein said at least one prompt definition in said one subset has the same ID as the prompt definition in the base subset to which it corresponds.
| 0.5 |
8,671,338 | 9 | 10 |
9. The method of claim 1 further comprising generating a second mark-up language document defining a second 3D scene based on the objects in memory.
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9. The method of claim 1 further comprising generating a second mark-up language document defining a second 3D scene based on the objects in memory. 10. The method of claim 9 , wherein the first 3D scene is the same as the second 3D scene.
| 0.5 |
8,633,838 | 1 | 18 |
1. A computer-implemented method of compressing data, comprising carrying out steps of the computer-implemented method by a computer system with at least a processor and a memory, the computer-implemented steps of the method including: a) receiving a current instance of data in memory comprising an input buffer; b) selecting a candidate chunk of a representation of the current instance from the input buffer; c) computing by the processor a signature hash from a signature length range of data starting in the candidate chunk; d) identifying a matching dictionary entry stored in memory having a matching signature hash from a multi-tiered dictionary, wherein the matching dictionary entry prospectively identifies a location of a prior occurrence of a selected range of consecutive symbols including the signature length range of data within at least one of the representation of the current instance of data and a representation of a prior instance of data in the input buffer; e) computing a dedupe processed representation of the instance of data in the input buffer, wherein a dedupe item is substituted for the selected range of consecutive symbols if the selected range is verified as recurring, wherein the dedupe item identifies the location of the prior occurrence of the selected range; and f) making the dedupe processed representation of the instance of data available for communication to a target computer.
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1. A computer-implemented method of compressing data, comprising carrying out steps of the computer-implemented method by a computer system with at least a processor and a memory, the computer-implemented steps of the method including: a) receiving a current instance of data in memory comprising an input buffer; b) selecting a candidate chunk of a representation of the current instance from the input buffer; c) computing by the processor a signature hash from a signature length range of data starting in the candidate chunk; d) identifying a matching dictionary entry stored in memory having a matching signature hash from a multi-tiered dictionary, wherein the matching dictionary entry prospectively identifies a location of a prior occurrence of a selected range of consecutive symbols including the signature length range of data within at least one of the representation of the current instance of data and a representation of a prior instance of data in the input buffer; e) computing a dedupe processed representation of the instance of data in the input buffer, wherein a dedupe item is substituted for the selected range of consecutive symbols if the selected range is verified as recurring, wherein the dedupe item identifies the location of the prior occurrence of the selected range; and f) making the dedupe processed representation of the instance of data available for communication to a target computer. 18. The computer-implemented method of claim 1 wherein the dictionary provides a single signature hash per dictionary entry.
| 0.833333 |
6,161,130 | 59 | 60 |
59. The apparatus in claim 57 wherein the message is an electronic mail (e-mail) message and said first and second classes are non-legitimate and legitimate messages, respectively.
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59. The apparatus in claim 57 wherein the message is an electronic mail (e-mail) message and said first and second classes are non-legitimate and legitimate messages, respectively. 60. The apparatus in claim 59 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize an e-mail message as belonging to the first class.
| 0.5 |
8,355,915 | 1 | 11 |
1. A multimodal system for receiving inputs via more than one mode from a user and for interpretation and display of text based upon the inputs received via the more than one modes, the system comprising: a) a user input device having a plurality of modes, one mode accepting speech input and the remaining modes accepting entry of non-speech input; b) a memory containing a plurality of acoustic networks, each of the plurality of acoustic networks being associated with at least one mode; and c) a processor to: i) process the speech input and at least one non-speech input accepted by at least one of the remaining modes; ii) dynamically adapting an acoustic network based on the speech input and the at least one non-speech input; iii) perform automatic speech recognition using the dynamically adapted acoustic network; iv) determine an output based on the automatic speech recognition; and v) return the output to aid in a determination of a subsequent user-action.
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1. A multimodal system for receiving inputs via more than one mode from a user and for interpretation and display of text based upon the inputs received via the more than one modes, the system comprising: a) a user input device having a plurality of modes, one mode accepting speech input and the remaining modes accepting entry of non-speech input; b) a memory containing a plurality of acoustic networks, each of the plurality of acoustic networks being associated with at least one mode; and c) a processor to: i) process the speech input and at least one non-speech input accepted by at least one of the remaining modes; ii) dynamically adapting an acoustic network based on the speech input and the at least one non-speech input; iii) perform automatic speech recognition using the dynamically adapted acoustic network; iv) determine an output based on the automatic speech recognition; and v) return the output to aid in a determination of a subsequent user-action. 11. The system of claim 1 , wherein the dynamically adapted acoustic network is compiled by the system during run-time.
| 0.674863 |
9,378,654 | 16 | 17 |
16. A system for rendering music notation comprising: one or more processors configured to: receive a request for electronic content, the request being communicated to the server by a client; obtain one or more files associated with the electronic content from a storage unit; parse one or more files associated with the electronic content to determine a music notation element; translate the music notation from a first format to a second format that is supported by a browser application; create a music notation object based at least in part on the translation; and send the music notation object to the client, wherein the client renders the music notation object via the browser application; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions.
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16. A system for rendering music notation comprising: one or more processors configured to: receive a request for electronic content, the request being communicated to the server by a client; obtain one or more files associated with the electronic content from a storage unit; parse one or more files associated with the electronic content to determine a music notation element; translate the music notation from a first format to a second format that is supported by a browser application; create a music notation object based at least in part on the translation; and send the music notation object to the client, wherein the client renders the music notation object via the browser application; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. 17. The system of claim 16 , wherein the one or more processors are further configured to translate the music notation to HTML containing Unicode characters.
| 0.521341 |
10,037,533 | 13 | 18 |
13. A non-transitory computer-readable storage medium having computer-executable instructions, which when executed perform a method comprising: retrieving a list of known fraudulent merchants; retrieving a plurality of historic cryptocurrency transactions; generating an electronic fingerprint for each fraudulent merchant of the known fraudulent merchants, based on one or more related transactions associated with the fraudulent merchant in the plurality of historic cryptocurrency transactions; identifying relationships between the known fraudulent merchants based on electronic fingerprints associated with the known fraudulent merchants; generating data representing a first graph based on the identified relationships; receiving a set of investigation information about a first merchant, the investigation information comprising an identification of the first merchant and one or more proposed cryptocurrency transactions associated with the first merchant; generating a first merchant electronic fingerprint for the first merchant based on the set of investigation information; performing via a query engine and based on the first merchant electronic fingerprint, a first query against the data representing the first graph to identify a first plurality of relationships of the first merchant to one or more of the known fraudulent merchants; determining that a first count of the identified first plurality of relationships of the first merchant to one or more of the known fraudulent merchants is above a first threshold; performing, using the query engine, a second query against the data representing the first graph to identify a second plurality of relationships of the first merchant to one or more of the known fraudulent merchants in the data representing the first graph; and rejecting via the computerized merchant fraud screening system, the one or more proposed cryptocurrency transactions in response to determining that a second count of the identified second plurality of relationships of the first merchant is above a second threshold.
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13. A non-transitory computer-readable storage medium having computer-executable instructions, which when executed perform a method comprising: retrieving a list of known fraudulent merchants; retrieving a plurality of historic cryptocurrency transactions; generating an electronic fingerprint for each fraudulent merchant of the known fraudulent merchants, based on one or more related transactions associated with the fraudulent merchant in the plurality of historic cryptocurrency transactions; identifying relationships between the known fraudulent merchants based on electronic fingerprints associated with the known fraudulent merchants; generating data representing a first graph based on the identified relationships; receiving a set of investigation information about a first merchant, the investigation information comprising an identification of the first merchant and one or more proposed cryptocurrency transactions associated with the first merchant; generating a first merchant electronic fingerprint for the first merchant based on the set of investigation information; performing via a query engine and based on the first merchant electronic fingerprint, a first query against the data representing the first graph to identify a first plurality of relationships of the first merchant to one or more of the known fraudulent merchants; determining that a first count of the identified first plurality of relationships of the first merchant to one or more of the known fraudulent merchants is above a first threshold; performing, using the query engine, a second query against the data representing the first graph to identify a second plurality of relationships of the first merchant to one or more of the known fraudulent merchants in the data representing the first graph; and rejecting via the computerized merchant fraud screening system, the one or more proposed cryptocurrency transactions in response to determining that a second count of the identified second plurality of relationships of the first merchant is above a second threshold. 18. The non-transitory computer-readable storage medium of claim 13 , wherein the method further comprises, extracting second data representing at least one condensed information graphlet from the first graph in response to performing the first query, wherein the first plurality of relationships are identified from the second data representing the graphlet.
| 0.668819 |
9,171,011 | 1 | 4 |
1. A method comprising: identifying, by one or more computing devices, a 3D model of an object from a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of the respective object; determining, by the one or more computing devices, whether a geographic coordinate of a point of interest is within the geographic area of the base polygon; when the geographic coordinate of the point of interest is within the geographic area of the base polygon, creating, by the one or more computing devices, a system tag including a search term selected based on the given point of interest; and associating, by the one or more computing devices, the system tag with the identified 3D model of the object.
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1. A method comprising: identifying, by one or more computing devices, a 3D model of an object from a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of the respective object; determining, by the one or more computing devices, whether a geographic coordinate of a point of interest is within the geographic area of the base polygon; when the geographic coordinate of the point of interest is within the geographic area of the base polygon, creating, by the one or more computing devices, a system tag including a search term selected based on the given point of interest; and associating, by the one or more computing devices, the system tag with the identified 3D model of the object. 4. The method of claim 1 , wherein the search term is a title of the given point of interest.
| 0.889549 |
8,954,374 | 15 | 17 |
15. A computer program product comprising a tangible computer readable recordable storage medium including computer useable program code for creating and enabling access to a community-augmented map, the computer program product including: computer useable program code for uploading user-generated content, wherein said user-generated content comprises content pertaining to one or more locations on a map and content pertaining to a relationship between the one or more locations and one or more additional locations on a map, and wherein said user-generated content comprises multiple modalities; computer useable program code for processing the user-generated content and storing the user-generated content in an intelligent knowledgebase; computer useable program code for applying one or more existing items of user-generated content from the intelligent knowledgebase to the uploaded user-generated content to infer one or more characteristics of one or more locations on the map based on the content pertaining to the relationship between the one or more locations in the uploaded user-generated content and the one or more additional locations on a map, wherein said one or more inferred characteristics are inferred from one or more human-originated non-numeric relationships, derived via one or more human community members, of the one or more locations relative to one or more surrounding locations; computer useable program code for retrieving the one or more inferred characteristics of the one or more locations on the map from the intelligent knowledgebase; computer useable program code for augmenting metadata on the map based on the one or more inferred characteristics, wherein said augmenting comprises (i) providing real-time information about one or more locations on the map, (ii) identifying one or more traversable routes between two or more locations on the map, and (iii) super-imposing user-generated content pertaining to one or more locations on the one or more traversable routes; and computer useable program code for outputting one of the one or more traversable routes in response to a query comprising a source location name and a destination location name, wherein said output traversable route comprises (i) a sequential list of multiple location names that represents a path traversal from the source location to the destination location and (ii) at least one inferred characteristic, from the one or more inferred characteristics, associated with each of the multiple location names in the sequential list.
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15. A computer program product comprising a tangible computer readable recordable storage medium including computer useable program code for creating and enabling access to a community-augmented map, the computer program product including: computer useable program code for uploading user-generated content, wherein said user-generated content comprises content pertaining to one or more locations on a map and content pertaining to a relationship between the one or more locations and one or more additional locations on a map, and wherein said user-generated content comprises multiple modalities; computer useable program code for processing the user-generated content and storing the user-generated content in an intelligent knowledgebase; computer useable program code for applying one or more existing items of user-generated content from the intelligent knowledgebase to the uploaded user-generated content to infer one or more characteristics of one or more locations on the map based on the content pertaining to the relationship between the one or more locations in the uploaded user-generated content and the one or more additional locations on a map, wherein said one or more inferred characteristics are inferred from one or more human-originated non-numeric relationships, derived via one or more human community members, of the one or more locations relative to one or more surrounding locations; computer useable program code for retrieving the one or more inferred characteristics of the one or more locations on the map from the intelligent knowledgebase; computer useable program code for augmenting metadata on the map based on the one or more inferred characteristics, wherein said augmenting comprises (i) providing real-time information about one or more locations on the map, (ii) identifying one or more traversable routes between two or more locations on the map, and (iii) super-imposing user-generated content pertaining to one or more locations on the one or more traversable routes; and computer useable program code for outputting one of the one or more traversable routes in response to a query comprising a source location name and a destination location name, wherein said output traversable route comprises (i) a sequential list of multiple location names that represents a path traversal from the source location to the destination location and (ii) at least one inferred characteristic, from the one or more inferred characteristics, associated with each of the multiple location names in the sequential list. 17. The computer program product of claim 15 , further comprising computer useable program code for updating information related to a location.
| 0.778638 |
7,971,186 | 1 | 2 |
1. A computer-implemented method for use in a computer programming environment, comprising: invoking a script; and determining an execution order for the invoked script predicated on the passing of parameters between scripted actions, comprising: selecting a first scripted action from a plurality of actions, wherein the plurality of actions are contemporaneously selectable with respect to the first scripted action; executing the first selected scripted action if sufficient parameter information is available to execute the selected first scripted action; selecting a second scripted action from the plurality of actions in response to determining that there is insufficient parameter information to execute the first selected scripted action; executing the second selected action and; wherein the second scripted action converts data from an incompatible data type into a compatible data type and wherein the scripted action are selected from candidate actions chosen according to a determination of relevance relative to previously chosen action and need for conversion of data to compatible data types.
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1. A computer-implemented method for use in a computer programming environment, comprising: invoking a script; and determining an execution order for the invoked script predicated on the passing of parameters between scripted actions, comprising: selecting a first scripted action from a plurality of actions, wherein the plurality of actions are contemporaneously selectable with respect to the first scripted action; executing the first selected scripted action if sufficient parameter information is available to execute the selected first scripted action; selecting a second scripted action from the plurality of actions in response to determining that there is insufficient parameter information to execute the first selected scripted action; executing the second selected action and; wherein the second scripted action converts data from an incompatible data type into a compatible data type and wherein the scripted action are selected from candidate actions chosen according to a determination of relevance relative to previously chosen action and need for conversion of data to compatible data types. 2. The computer-implemented method of claim 1 , further comprising executing a third selected action from the plurality of actions.
| 0.770175 |
8,941,589 | 90 | 91 |
90. The system of claim 89 , wherein the ATC automatically determines the at least one location.
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90. The system of claim 89 , wherein the ATC automatically determines the at least one location. 91. The system of claim 90 , wherein location data of the at least one location is manually entered.
| 0.5 |
8,024,183 | 12 | 13 |
12. A method for audio classification, comprising: providing a plurality of transforms for decoding utterances, wherein the transforms correspond to a plurality of input types; and applying one of the transforms to a speaker using a processor based upon the input type; wherein the transforms are precomputed by: maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under a target channel condition state; and transforming, based on said best transformation, features of a speaker utterance in a source channel condition state to match the target channel condition state and as a result provide a channel matched transformed utterance.
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12. A method for audio classification, comprising: providing a plurality of transforms for decoding utterances, wherein the transforms correspond to a plurality of input types; and applying one of the transforms to a speaker using a processor based upon the input type; wherein the transforms are precomputed by: maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under a target channel condition state; and transforming, based on said best transformation, features of a speaker utterance in a source channel condition state to match the target channel condition state and as a result provide a channel matched transformed utterance. 13. The method as recited in claim 12 , wherein the best transform is determined for each input type and applied by determining conditions under which a speaker is providing input.
| 0.723077 |
9,311,295 | 1 | 6 |
1. A method for extraction and enrichment of a procedure from an unstructured text document, comprising: identifying a potential location of a procedure in the unstructured text document; detecting a beginning boundary and an end boundary associated with the identified potential location of the procedure; validating a text associated with the identified potential location of the procedure in the unstructured text document; determining an intent from the identified potential location of the procedure based on at least one of the beginning boundary, the end boundary, a surrounding text associated with the identified potential location of the procedure, a context associated with the unstructured text document, and a title of the unstructured text document; and enriching the procedure based on the determined intent; identifying a plurality of paths in the unstructured text document that lead to a same step in the procedure, wherein the identified plurality of paths are located outside the identified beginning boundary and the identified end boundary; and annotating the identified plurality of paths, wherein annotating the identified plurality of paths comprises determining an input/output relation of the identified plurality of paths and storing the determined input/output relation inside the unstructured text document and in a database.
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1. A method for extraction and enrichment of a procedure from an unstructured text document, comprising: identifying a potential location of a procedure in the unstructured text document; detecting a beginning boundary and an end boundary associated with the identified potential location of the procedure; validating a text associated with the identified potential location of the procedure in the unstructured text document; determining an intent from the identified potential location of the procedure based on at least one of the beginning boundary, the end boundary, a surrounding text associated with the identified potential location of the procedure, a context associated with the unstructured text document, and a title of the unstructured text document; and enriching the procedure based on the determined intent; identifying a plurality of paths in the unstructured text document that lead to a same step in the procedure, wherein the identified plurality of paths are located outside the identified beginning boundary and the identified end boundary; and annotating the identified plurality of paths, wherein annotating the identified plurality of paths comprises determining an input/output relation of the identified plurality of paths and storing the determined input/output relation inside the unstructured text document and in a database. 6. The method of claim 1 , wherein the determining the intent from the identified potential location of the procedure comprises annotating the procedure with the determined intent.
| 0.72561 |
9,311,361 | 1 | 4 |
1. A computer-implemented method for automatically determining a visual appeal of online content, the method implemented using a visual appeal determination computing device coupled to a user interface and a memory device, the method comprising: storing, by the visual appeal determination computing device, a plurality of software implemented algorithms in the memory device, each algorithm comprising one or more rules representing expert knowledge for subject matter of online content items, the rules are capable of recognizing graphic content parameters, recognizing textual content parameters, and relating the graphic content parameters and the textual content parameters to a set of desired parameters accessible to the rules based on the expert knowledge, the parameters relating to the appearance of the graphic content and the textual content, each algorithm pertains to a different aspect of online content; receiving, by the visual appeal determination computing device, one or more generated items of online content from a content provider computing device; determining, by the visual appeal determination computing device, graphic content parameters and textual content parameters of the received items of online content by parsing the online content using the plurality of algorithms according to the different rules included in each algorithm, determining the graphic content parameters and textual content parameters include determining a relative size of a font with respect to other textual content, a location of the textual content within the content item, a location of breaks used in text wrapping in the textual content, a relative alignment of the textual content, a readability of the textual content based on font colors and background colors, and an orientation of graphic objects within the content item; comparing, by the visual appeal determination computing device, the determined parameters to the set of desired parameters by determining whether each aspect meets a respective predefined threshold value; ranking, by the visual appeal determination computing device, the items of online content based on the comparisons; and providing guidance for improving a quality of the items of online content by outputting, by the visual appeal determination computing device, the ranked items of online content to the content provider computing device.
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1. A computer-implemented method for automatically determining a visual appeal of online content, the method implemented using a visual appeal determination computing device coupled to a user interface and a memory device, the method comprising: storing, by the visual appeal determination computing device, a plurality of software implemented algorithms in the memory device, each algorithm comprising one or more rules representing expert knowledge for subject matter of online content items, the rules are capable of recognizing graphic content parameters, recognizing textual content parameters, and relating the graphic content parameters and the textual content parameters to a set of desired parameters accessible to the rules based on the expert knowledge, the parameters relating to the appearance of the graphic content and the textual content, each algorithm pertains to a different aspect of online content; receiving, by the visual appeal determination computing device, one or more generated items of online content from a content provider computing device; determining, by the visual appeal determination computing device, graphic content parameters and textual content parameters of the received items of online content by parsing the online content using the plurality of algorithms according to the different rules included in each algorithm, determining the graphic content parameters and textual content parameters include determining a relative size of a font with respect to other textual content, a location of the textual content within the content item, a location of breaks used in text wrapping in the textual content, a relative alignment of the textual content, a readability of the textual content based on font colors and background colors, and an orientation of graphic objects within the content item; comparing, by the visual appeal determination computing device, the determined parameters to the set of desired parameters by determining whether each aspect meets a respective predefined threshold value; ranking, by the visual appeal determination computing device, the items of online content based on the comparisons; and providing guidance for improving a quality of the items of online content by outputting, by the visual appeal determination computing device, the ranked items of online content to the content provider computing device. 4. The method of claim 1 , wherein comparing the determined parameters to the set of desired parameters comprises comparing the determined parameters to the set of desired parameters that include a first definition of acceptable combinations of parameters and a second definition of incompatible combinations of parameters.
| 0.66 |
8,538,081 | 11 | 12 |
11. The non-transitory computer-readable medium or media of claim 10 further comprising: generating a contextual boost feature for the image window comprising the one or more image features extracted from the image window and from the set of neighboring image windows and the classification context feature.
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11. The non-transitory computer-readable medium or media of claim 10 further comprising: generating a contextual boost feature for the image window comprising the one or more image features extracted from the image window and from the set of neighboring image windows and the classification context feature. 12. The non-transitory computer-readable medium or media of claim 11 further comprising: augmenting the contextual boost feature for the image window by iteratively adding an updated classification context feature to the contextual boost feature of an immediately prior iteration until a stop condition has been reached.
| 0.5 |
8,332,399 | 13 | 15 |
13. A non-transitory computer-readable memory device storing instructions that are executable by one or more processors of one or more devices, the instructions including: one or more instructions to extract, from each document, of a plurality of documents, only one title to obtain a plurality of titles, where a particular title of a particular document includes a label or identifying data identifying the particular document, and where each document, of the plurality of documents, is associated with only one title; one or more instructions to count a quantity of times that particular words occur within the plurality of titles, one or more instructions to compute a score for each title of the plurality of titles, where the plurality of titles and the computed scores are associated with a particular time period, and where the score for each title is derived from the quantity of times that the particular words occur within the plurality of titles, and a quantity of words, included in the selected words, that are included in the each title, and one or more instructions to select one title from the plurality of titles, based on the computed scores associated with the particular time period, where the particular time period is associated with a portion of a particular time interval, where the score associated with the one title is a first score, where the particular time interval includes another time period that is associated with a second score that exceeds the first score, and where a quantity of times the selected words occur in titles, that are associated with the other time period, exceeds a quantity of times the selected words occur in the plurality of titles that are associated with the particular time period.
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13. A non-transitory computer-readable memory device storing instructions that are executable by one or more processors of one or more devices, the instructions including: one or more instructions to extract, from each document, of a plurality of documents, only one title to obtain a plurality of titles, where a particular title of a particular document includes a label or identifying data identifying the particular document, and where each document, of the plurality of documents, is associated with only one title; one or more instructions to count a quantity of times that particular words occur within the plurality of titles, one or more instructions to compute a score for each title of the plurality of titles, where the plurality of titles and the computed scores are associated with a particular time period, and where the score for each title is derived from the quantity of times that the particular words occur within the plurality of titles, and a quantity of words, included in the selected words, that are included in the each title, and one or more instructions to select one title from the plurality of titles, based on the computed scores associated with the particular time period, where the particular time period is associated with a portion of a particular time interval, where the score associated with the one title is a first score, where the particular time interval includes another time period that is associated with a second score that exceeds the first score, and where a quantity of times the selected words occur in titles, that are associated with the other time period, exceeds a quantity of times the selected words occur in the plurality of titles that are associated with the particular time period. 15. The computer-readable memory device of claim 13 , further comprising: one or more instructions to receive a query; one or more instructions to count a number of occurrences of at least a portion of the query in the plurality of titles; one or more instructions to plot the number of occurrences on a graph; and one or more instructions to label the plotted number of occurrences with the selected title.
| 0.5 |
9,818,032 | 18 | 19 |
18. The at least one machine readable medium of claim 17 , wherein generating the semantic model includes extracting features of the frames.
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18. The at least one machine readable medium of claim 17 , wherein generating the semantic model includes extracting features of the frames. 19. The at least one machine readable medium of claim 18 , wherein generating the semantic model includes generating a pseudo-semantic domain from the extracted features, wherein the pseudo-semantic domain is an n-dimensional space derived from the features.
| 0.5 |
6,049,796 | 1 | 4 |
1. A method for operating a personal digital assistant having an input means, a file storage means, a data base, a search engine means, a display means, and an electronic communication means, comprising the steps of: storing in the data base one or more records, each of the records comprising data elements defining an identifier of a party and communication information required for communicating with the party through a communication link; in response to an input from a user, selecting one of a plurality of directories, each of said directories comprising one or more entries and being related to a respective type of communication, each of said entries corresponding to at least one of said data elements of one of said records; in response to the selecting step, displaying each of the one or more entries of the selected directory; inputting a search key corresponding to at least a portion of at least one of the displayed entries of the selected directory; comparing the search key to at least one data element corresponding to at least one of the displayed entries and further displaying those ones of the entries which correspond to data elements corresponding to the search key; and in response to another input by the user, selecting one of the further displayed entries for initiating a communication to a party, the party being identified by the identifier defined by data elements corresponding to the selected entry.
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1. A method for operating a personal digital assistant having an input means, a file storage means, a data base, a search engine means, a display means, and an electronic communication means, comprising the steps of: storing in the data base one or more records, each of the records comprising data elements defining an identifier of a party and communication information required for communicating with the party through a communication link; in response to an input from a user, selecting one of a plurality of directories, each of said directories comprising one or more entries and being related to a respective type of communication, each of said entries corresponding to at least one of said data elements of one of said records; in response to the selecting step, displaying each of the one or more entries of the selected directory; inputting a search key corresponding to at least a portion of at least one of the displayed entries of the selected directory; comparing the search key to at least one data element corresponding to at least one of the displayed entries and further displaying those ones of the entries which correspond to data elements corresponding to the search key; and in response to another input by the user, selecting one of the further displayed entries for initiating a communication to a party, the party being identified by the identifier defined by data elements corresponding to the selected entry. 4. A method as described in claim 1, wherein prior to the step of inputting the search key, a step is performed of inputting a message into the personal digital assistant through the input means, and wherein the communication initiated in the step of selecting one of the further displayed entries communicates the inputted message to the party identified by the identifier defined by data elements corresponding to the selected entry.
| 0.788012 |
8,291,039 | 5 | 7 |
5. A method of transferring data via a communication session between a client application on a first network and a server application on a second network, the method comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application on the second network is behind a second firewall that is different from the first firewall.
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5. A method of transferring data via a communication session between a client application on a first network and a server application on a second network, the method comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application on the second network is behind a second firewall that is different from the first firewall. 7. The method of claim 5 , wherein the local protocol comprises at least one of TCP/IP and a serial protocol, the serial protocol comprising one of RS232 and RS485.
| 0.579487 |
7,617,179 | 1 | 21 |
1. In a database system, a method for optimizing a database query for execution by a processor, the method comprising: receiving a database query including at least one subquery; building a query optimization graph for each query block of the database query, the query optimization graph including plan nodes representing subqueries of each query block; prior to optimization of a query block, identifying alternative strategies for evaluation of a subquery plan node of the query block based on subquery type and semantic properties of the database query; for each alternative strategy, pre-computing a subquery access method and subquery join method for use during optimization of the query block, wherein the subquery access method includes an estimate of execution costs; generating a set of access methods and join methods for other plan nodes of the query block; optimizing each query block to determine an optimal access plan for the query block based upon selecting pre-computed subquery access methods and join methods for subquery plan nodes of the query block as well as access methods, join methods, and join order for other plan nodes of the query block having favorable execution costs, wherein each query block is optimized without transformation of the subqueries using the pre-computed access methods and join methods; and constructing a detailed access plan for execution of the database query based upon the optimal access plan determined for each query block.
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1. In a database system, a method for optimizing a database query for execution by a processor, the method comprising: receiving a database query including at least one subquery; building a query optimization graph for each query block of the database query, the query optimization graph including plan nodes representing subqueries of each query block; prior to optimization of a query block, identifying alternative strategies for evaluation of a subquery plan node of the query block based on subquery type and semantic properties of the database query; for each alternative strategy, pre-computing a subquery access method and subquery join method for use during optimization of the query block, wherein the subquery access method includes an estimate of execution costs; generating a set of access methods and join methods for other plan nodes of the query block; optimizing each query block to determine an optimal access plan for the query block based upon selecting pre-computed subquery access methods and join methods for subquery plan nodes of the query block as well as access methods, join methods, and join order for other plan nodes of the query block having favorable execution costs, wherein each query block is optimized without transformation of the subqueries using the pre-computed access methods and join methods; and constructing a detailed access plan for execution of the database query based upon the optimal access plan determined for each query block. 21. The method of claim 1 , further comprising: Processor-executable instructions stored on a computer-readable medium for performing the method of claim 1 .
| 0.772464 |
10,146,813 | 1 | 13 |
1. A method comprising: receiving a query; processing a global index associated with a database with respect to the query to identify one or more identifiers within the global index that correspond to the query; based on an identification of the one or more identifiers within the global index that correspond to the query, processing, by a processing device, one or more indexes associated with one or more data items within the database with respect to the one or more identifiers; based on an identification of a presence of the one or more identifiers within a row of at least one of the one or more indexes, scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more identifiers; based on a scan of the one or more rows of the at least one of the one or more indexes, identifying one or more other identifiers within the one or more rows that are associated with the one or more identifiers; scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more other identifiers; based on the scanning of the one or more rows, identifying one or more search results in response to the query; prioritizing the one or more search results based on one or more respective priority status indicators associated with the one or more search results; and providing the one or more search results, as prioritized, in response to the query.
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1. A method comprising: receiving a query; processing a global index associated with a database with respect to the query to identify one or more identifiers within the global index that correspond to the query; based on an identification of the one or more identifiers within the global index that correspond to the query, processing, by a processing device, one or more indexes associated with one or more data items within the database with respect to the one or more identifiers; based on an identification of a presence of the one or more identifiers within a row of at least one of the one or more indexes, scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more identifiers; based on a scan of the one or more rows of the at least one of the one or more indexes, identifying one or more other identifiers within the one or more rows that are associated with the one or more identifiers; scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more other identifiers; based on the scanning of the one or more rows, identifying one or more search results in response to the query; prioritizing the one or more search results based on one or more respective priority status indicators associated with the one or more search results; and providing the one or more search results, as prioritized, in response to the query. 13. The method of claim 1 , wherein the one or more identifiers comprises at least one of: a temporal identifier, a relevancy identifier, or an accessibility identifier.
| 0.825413 |
8,312,102 | 7 | 8 |
7. The method according to claim 1 further comprising: importing the content package file to a portal server computer.
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7. The method according to claim 1 further comprising: importing the content package file to a portal server computer. 8. The method according to claim 7 further comprising: storing the content package file and the first level content files on the portal server computer, wherein the first level content files overwrite duplicative files that are stored on the portal server computer.
| 0.512868 |
10,061,850 | 17 | 23 |
17. A system for providing search results to a first user of a client, the system comprising: one or more processors; memory coupled to the processor, the memory storing program modules executable by the processors, the program modules including: a receiving module configured to receive a first query for one or more items of interest and a navigational query for a first website, wherein the first query includes at least one search term, and wherein the navigational query includes a first identifier of the first web site, and the at least one search term is absent from the navigational query; an execution module configured to: obtain and store results responsive to the first query prior to receiving the navigation query, wherein the first query is a recent query of the navigation query, after obtaining and storing the results responsive to the recent query, in response to receiving the navigational query, obtain the at least one search term from the recent query, and execute an alternate query of the first web site to yield alternate search results responsive to the alternate query within a domain of the first website, the alternate query including the at least one search term and the navigational query; and a transmitting module configured to transmit to the first user the alternate search results, at least one top ranking navigational search result, and at least one remaining navigational search result for display, wherein the at least one top ranking navigational search result, the alternate search results, and the at least one remaining navigational search result are associated with a priority attribute that indicates a priority level for display, wherein a first priority attribute is associated with the at least one top ranking navigational search result and indicates that the at least one top ranking navigational search result is to be displayed above other search results displayed on a search result page, a second priority attribute is associated with the alternate query search result and indicates that the alternate query search result is to be displayed below the at least one top ranking navigational search result in the search result page, and a third priority attribute is associated with the at least one remaining navigational search result and indicates that the at least one remaining navigational search result is to be displayed below the alternate query search result in the search result page, the first priority attribute having a highest priority level and the third priority attribute having a lowest priority level.
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17. A system for providing search results to a first user of a client, the system comprising: one or more processors; memory coupled to the processor, the memory storing program modules executable by the processors, the program modules including: a receiving module configured to receive a first query for one or more items of interest and a navigational query for a first website, wherein the first query includes at least one search term, and wherein the navigational query includes a first identifier of the first web site, and the at least one search term is absent from the navigational query; an execution module configured to: obtain and store results responsive to the first query prior to receiving the navigation query, wherein the first query is a recent query of the navigation query, after obtaining and storing the results responsive to the recent query, in response to receiving the navigational query, obtain the at least one search term from the recent query, and execute an alternate query of the first web site to yield alternate search results responsive to the alternate query within a domain of the first website, the alternate query including the at least one search term and the navigational query; and a transmitting module configured to transmit to the first user the alternate search results, at least one top ranking navigational search result, and at least one remaining navigational search result for display, wherein the at least one top ranking navigational search result, the alternate search results, and the at least one remaining navigational search result are associated with a priority attribute that indicates a priority level for display, wherein a first priority attribute is associated with the at least one top ranking navigational search result and indicates that the at least one top ranking navigational search result is to be displayed above other search results displayed on a search result page, a second priority attribute is associated with the alternate query search result and indicates that the alternate query search result is to be displayed below the at least one top ranking navigational search result in the search result page, and a third priority attribute is associated with the at least one remaining navigational search result and indicates that the at least one remaining navigational search result is to be displayed below the alternate query search result in the search result page, the first priority attribute having a highest priority level and the third priority attribute having a lowest priority level. 23. The system of claim 17 , wherein the search results for the alternate query further include a search result in the search results for the recent query.
| 0.864983 |
8,869,072 | 1 | 5 |
1. A method for providing gesture input to a plurality of applications, comprising: receiving data indicative of a user motion or pose, the data being captured by a camera; determining a result of processing the data, the result comprising a three-dimensional model of at least part of the user; sending the result to a first gesture filter of a first application of the plurality of applications, the first application being configured to process the result with the first gesture filter to determine a first output indicative of whether the result is indicative of the user performing a gesture represented by the first gesture filter; and sending the result to a second gesture filter of a second application of the plurality of applications, the second application being configured to process the result with the second gesture filter to determine a second output indicative of whether the result is indicative of the user performing a gesture represented by the second gesture filter.
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1. A method for providing gesture input to a plurality of applications, comprising: receiving data indicative of a user motion or pose, the data being captured by a camera; determining a result of processing the data, the result comprising a three-dimensional model of at least part of the user; sending the result to a first gesture filter of a first application of the plurality of applications, the first application being configured to process the result with the first gesture filter to determine a first output indicative of whether the result is indicative of the user performing a gesture represented by the first gesture filter; and sending the result to a second gesture filter of a second application of the plurality of applications, the second application being configured to process the result with the second gesture filter to determine a second output indicative of whether the result is indicative of the user performing a gesture represented by the second gesture filter. 5. The method of claim 1 , further comprising: before receiving the data indicative of the user motion or pose, receiving second data indicative of a second user motion or pose; and sending the second data to the first application of the plurality of applications, the first application being configured to modify how the first gesture filter recognizes the gesture represented by the first gesture filter based on the second data.
| 0.778292 |
8,825,627 | 10 | 11 |
10. The computer-implemented method of claim 9 , wherein utilizing the identified keywords to identify a product category comprises comparing the keywords associated with the requested page to keywords associated with the product categories to identify the product category.
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10. The computer-implemented method of claim 9 , wherein utilizing the identified keywords to identify a product category comprises comparing the keywords associated with the requested page to keywords associated with the product categories to identify the product category. 11. The computer-implemented method of claim 10 , further comprising classifying one or more of the products into one or more sub-categories of the product categories and to storing an association between each of the sub-categories and at least one of the themes.
| 0.586478 |
9,911,420 | 16 | 18 |
16. The system of claim 15 , wherein determining that the restricted, canonical pronunciation of the particular term by the user is not age appropriate, the operations further comprise selecting a remediation strategy for inducing the user to speak the particular term using an age appropriate pronunciation.
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16. The system of claim 15 , wherein determining that the restricted, canonical pronunciation of the particular term by the user is not age appropriate, the operations further comprise selecting a remediation strategy for inducing the user to speak the particular term using an age appropriate pronunciation. 18. The system of claim 16 , wherein the remediation strategy for inducing the user to speak the particular term using an age-appropriate pronunciation involves initiating an action associated with the particular term despite the determination that the pronunciation of the particular term by the user is not age-appropriate and a determination that the user in a state of high anxiety or stress.
| 0.5 |
8,862,474 | 10 | 11 |
10. The computer-implemented method of claim 1 , further comprising: in response to initiating the first audio recording process, outputting an indication on the mobile computing device that indicates that the first audio recording process has started.
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10. The computer-implemented method of claim 1 , further comprising: in response to initiating the first audio recording process, outputting an indication on the mobile computing device that indicates that the first audio recording process has started. 11. The computer-implemented method of claim 10 , further comprising: in response to stopping the first audio recording process, outputting another indication on the mobile computing device that indicates that the first audio recording process has stopped.
| 0.5 |
8,396,878 | 1 | 8 |
1. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; and generating a heat map for the video file, wherein the heat map comprises a graphical display which indicates offset locations of words within the video file with the highest rankings, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words.
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1. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; and generating a heat map for the video file, wherein the heat map comprises a graphical display which indicates offset locations of words within the video file with the highest rankings, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. 8. The computer-implemented method of generating automated tags for the video file as in claim 1 , wherein the video file includes an associated audio file, wherein the targeted transcript comprise the plurality of words extracted from the audio file, and wherein each of the plurality of words has an associated offset value which designates the occurrence position of each word within the video file.
| 0.803519 |
8,990,208 | 11 | 12 |
11. The method of claim 10 , further comprising: calculating a correlation coefficient based on: an average interest score of the plurality of common-interest information topics from the first user, a second average interest score of the plurality of common-interest information topics from the second user, the interest score of each interest of the plurality of common-interest information topics from the first user, and the second interest score of each interest of the plurality of common-interest information topics from the second user.
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11. The method of claim 10 , further comprising: calculating a correlation coefficient based on: an average interest score of the plurality of common-interest information topics from the first user, a second average interest score of the plurality of common-interest information topics from the second user, the interest score of each interest of the plurality of common-interest information topics from the first user, and the second interest score of each interest of the plurality of common-interest information topics from the second user. 12. The method of claim 11 , wherein the common-interest strength is also calculated using the correlation coefficient of the first user and the second user.
| 0.5 |
8,068,007 | 7 | 9 |
7. A method for generating a credential for an emergency responder to participate in an operation, the method comprising: storing credentialing data in a data store, the credentialing data comprising identification data, licensing data, and skills and training certification data for a plurality of emergency responders for a plurality of agencies, each of the plurality of agencies providing an emergency response service; generating a verification of identify request at a credentialing terminal in response to an input, the verification of identify request comprising identification data for a particular emergency responder; retrieving credentialing data from the data store at a credentialing computing device to verify the identity and to verify the qualifications of the particular emergency responder in response to the verification of identify request; generating a credential generation request for the particular emergency responder at the credentialing computing device in response to a verified identity and verified qualifications; and generating the credential for the particular emergency responder at the credentialing terminal in response to a verified identity and verified qualifications; and wherein the credential comprises a record of the verified identity and the verified qualifications of the particular emergency responder.
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7. A method for generating a credential for an emergency responder to participate in an operation, the method comprising: storing credentialing data in a data store, the credentialing data comprising identification data, licensing data, and skills and training certification data for a plurality of emergency responders for a plurality of agencies, each of the plurality of agencies providing an emergency response service; generating a verification of identify request at a credentialing terminal in response to an input, the verification of identify request comprising identification data for a particular emergency responder; retrieving credentialing data from the data store at a credentialing computing device to verify the identity and to verify the qualifications of the particular emergency responder in response to the verification of identify request; generating a credential generation request for the particular emergency responder at the credentialing computing device in response to a verified identity and verified qualifications; and generating the credential for the particular emergency responder at the credentialing terminal in response to a verified identity and verified qualifications; and wherein the credential comprises a record of the verified identity and the verified qualifications of the particular emergency responder. 9. The method of claim 7 wherein the generated credential comprises a smart card comprising a storage media for storing verified identity and verified qualifications data.
| 0.807432 |
8,972,460 | 15 | 17 |
15. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process to implement data model optimization using multilevel entity dependency analytics, the process comprising: accessing a multilevel schema data structure; determining a dependency relationship lineage between schema entities present in the multilevel schema data structure; generating a dependency table using the dependency relationship lineage, the dependency table comprising at least one multilevel dependency relationship between schema entities having a depth of two or more; using the dependency table to perform at least one analysis comprising at least one of, a high impact analysis, a referential integrity analysis, or a conformance analysis; and storing a result from the analysis in a stored metadata format.
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15. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process to implement data model optimization using multilevel entity dependency analytics, the process comprising: accessing a multilevel schema data structure; determining a dependency relationship lineage between schema entities present in the multilevel schema data structure; generating a dependency table using the dependency relationship lineage, the dependency table comprising at least one multilevel dependency relationship between schema entities having a depth of two or more; using the dependency table to perform at least one analysis comprising at least one of, a high impact analysis, a referential integrity analysis, or a conformance analysis; and storing a result from the analysis in a stored metadata format. 17. The computer program product of claim 15 , wherein the stored metadata format is at least one of, an XML format, a binary format, a message format, or a relational database table.
| 0.5 |
8,266,068 | 1 | 10 |
1. A method to interview a candidate, comprising: providing a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtaining a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjusting the interview plan to generate an adjusted interview plan based on the qualified candidate profile and the pre-determined qualification score; collecting, using the processor, a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyzing the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively presenting the candidate profile information to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information.
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1. A method to interview a candidate, comprising: providing a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtaining a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjusting the interview plan to generate an adjusted interview plan based on the qualified candidate profile and the pre-determined qualification score; collecting, using the processor, a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyzing the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively presenting the candidate profile information to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information. 10. The method of claim 1 , further comprising providing environmental stimulus to the candidate for gauging a response from the candidate.
| 0.919653 |
8,539,347 | 1 | 6 |
1. A method for presenting a time sequence of editing steps in a two-dimensional document, the method comprising: accepting, at a first time on an electronic document editing device, a first editing command for a first two-dimensional object within a two-dimensional electronic document, the two-dimensional electronic document defining objects with a first dimension and a second dimension; accepting, at the electronic document editing device at a second time subsequent to the first time, a second editing command specifying a modification to a definition of the first two-dimensional object within at least one of the first dimension and the second dimension; and displaying, on a display device, a representation of a three-dimensional structure corresponding to the first two-dimensional object, the three-dimensional structure depicting at least one of the first dimension and the second dimension and representing time as a third dimension that is orthogonal to the first dimension and the second dimension, the three-dimensional structure representing a time interval between the first time and the second time as structural elements extending along the third dimension, the three-dimensional structure extending along the third dimension from a first time point corresponding to the first time to a second time point corresponding to the second time, the three-dimensional structure having components at the first time point in the first dimension and the second dimension that represent a view of the first two-dimensional object, the three-dimensional structure having components at the second time point in the first dimension and the second dimension that represent a view of the second two-dimensional object, the structural elements extending along the third dimension from the view of the first two-dimensional object to the view of the second two-dimensional object, the structural elements representing the modification to the definition of the first two-dimensional object as specified by the second editing command, the structural elements extending along the third dimension with first dimension components and second dimension components corresponding to the first editing command, and three-dimensional structure representing a time interval subsequent to the second time as a subsequent three-dimensional object representing the first two-dimensional object as modified by the second editing command, the subsequent three-dimensional object having subsequent first dimension components and subsequent second dimension components corresponding to the second editing command and extended along the third dimension, accepting, at a third time that is subsequent to the second time, a command specifying a modification to the first editing command; and updating, in response to accepting the command specifying the modification to the first editing command, the three-dimensional structure to reflect, at a point corresponding to the first time within the three-dimensional structure, the modification of the first editing command, the updating further modifying the three dimensional structure along the third dimension to reflect the modification of the first editing command.
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1. A method for presenting a time sequence of editing steps in a two-dimensional document, the method comprising: accepting, at a first time on an electronic document editing device, a first editing command for a first two-dimensional object within a two-dimensional electronic document, the two-dimensional electronic document defining objects with a first dimension and a second dimension; accepting, at the electronic document editing device at a second time subsequent to the first time, a second editing command specifying a modification to a definition of the first two-dimensional object within at least one of the first dimension and the second dimension; and displaying, on a display device, a representation of a three-dimensional structure corresponding to the first two-dimensional object, the three-dimensional structure depicting at least one of the first dimension and the second dimension and representing time as a third dimension that is orthogonal to the first dimension and the second dimension, the three-dimensional structure representing a time interval between the first time and the second time as structural elements extending along the third dimension, the three-dimensional structure extending along the third dimension from a first time point corresponding to the first time to a second time point corresponding to the second time, the three-dimensional structure having components at the first time point in the first dimension and the second dimension that represent a view of the first two-dimensional object, the three-dimensional structure having components at the second time point in the first dimension and the second dimension that represent a view of the second two-dimensional object, the structural elements extending along the third dimension from the view of the first two-dimensional object to the view of the second two-dimensional object, the structural elements representing the modification to the definition of the first two-dimensional object as specified by the second editing command, the structural elements extending along the third dimension with first dimension components and second dimension components corresponding to the first editing command, and three-dimensional structure representing a time interval subsequent to the second time as a subsequent three-dimensional object representing the first two-dimensional object as modified by the second editing command, the subsequent three-dimensional object having subsequent first dimension components and subsequent second dimension components corresponding to the second editing command and extended along the third dimension, accepting, at a third time that is subsequent to the second time, a command specifying a modification to the first editing command; and updating, in response to accepting the command specifying the modification to the first editing command, the three-dimensional structure to reflect, at a point corresponding to the first time within the three-dimensional structure, the modification of the first editing command, the updating further modifying the three dimensional structure along the third dimension to reflect the modification of the first editing command. 6. The method of claim 1 , further comprising: accepting, at the electronic document editing device at a third time subsequent to the first time, a third editing command for a second two-dimensional object within the two-dimensional electronic document; and displaying, on the display device, a representation of an additional three-dimensional structure corresponding to the second two-dimensional object along with the three-dimensional representation of the first two-dimensional object, the additional three-dimensional structure extending along the third dimension from a third time point corresponding to the third time, the additional three-dimensional structure depicting at least one of the first dimension and the second dimension and representing time as a third dimension illustrated as being orthogonal to the first dimension and the second dimension, the additional three-dimensional structure representing first dimension components and second dimension components corresponding to the third editing command at the third time point and extending from the third time point.
| 0.708735 |
8,554,558 | 1 | 5 |
1. An automated speech processing method comprising: using a speech-to-text (STT) engine for receiving an audio input and for converting the audio input to text data in a source language; using a machine translation (MT) engine for receiving the text data from the STT engine and for translating the text data to text data in a target language; using a caption engine for rendering the text data in the target language on a display device, including receiving metadata from the STT engine and the MT engine identifying defined characteristics of specific portions of the rendered text data in the target language including a defined confidence value representing the accuracy of the rendered text data based on both the accuracy of the converting the audio input to text data in the source language and the accuracy of translating the text data including interactions between the STT engine and MT engine comprising alignment information, and determining specific portions of the text data in the target language to which said defined characteristics, identified by the metadata from the STT engine, apply; and applying different visualization schemes based on color, font, size, underlining and italicization to different parts of the rendered text data based on the defined characteristics of the metadata.
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1. An automated speech processing method comprising: using a speech-to-text (STT) engine for receiving an audio input and for converting the audio input to text data in a source language; using a machine translation (MT) engine for receiving the text data from the STT engine and for translating the text data to text data in a target language; using a caption engine for rendering the text data in the target language on a display device, including receiving metadata from the STT engine and the MT engine identifying defined characteristics of specific portions of the rendered text data in the target language including a defined confidence value representing the accuracy of the rendered text data based on both the accuracy of the converting the audio input to text data in the source language and the accuracy of translating the text data including interactions between the STT engine and MT engine comprising alignment information, and determining specific portions of the text data in the target language to which said defined characteristics, identified by the metadata from the STT engine, apply; and applying different visualization schemes based on color, font, size, underlining and italicization to different parts of the rendered text data based on the defined characteristics of the metadata. 5. The method according to claim 1 , wherein the applying different visualization schemes includes applying a selected one of the visualization schemes to a selected part of the rendered text data that corresponds to one or more of the words in the source language that have a STT confidence value below a given threshold value.
| 0.50152 |
9,805,128 | 1 | 2 |
1. A method for determining a psychological type of a user, the method comprising: assigning, by one or more processors, based on a personality type indicator, a plurality of weightages to a plurality of attributes associated with a profile of said user on a social media platform; determining, by said one or more processors, a first score associated with said user based on said assigned plurality of weightages; determining, by said one or more processors, a second score associated with said user based on one or more activities of said user on said social media platform; determining, by said one or more processors, a part of speech associated with each word of a plurality of words in one or more conversations of said user on said social media platform, wherein said determination of said part of speech is based on a context database; categorizing, by said one or more processors, said each word of said plurality of words in one or more categories based on said part of speech associated with said each word; determining, by said one or more processors, context of said one or more conversations based on said categorization; determining, by said one or more processors, a third score associated with said user based on said context of said one or more conversations; determining, by said one or more processors, said psychological type of said user based on said first score, said second score, and said third score; and transmitting information, by said one or more processors, based on said determined psychological type, wherein said information indicates at least one of promotional offers, advertisements, marketing strategies, or publicity strategies.
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1. A method for determining a psychological type of a user, the method comprising: assigning, by one or more processors, based on a personality type indicator, a plurality of weightages to a plurality of attributes associated with a profile of said user on a social media platform; determining, by said one or more processors, a first score associated with said user based on said assigned plurality of weightages; determining, by said one or more processors, a second score associated with said user based on one or more activities of said user on said social media platform; determining, by said one or more processors, a part of speech associated with each word of a plurality of words in one or more conversations of said user on said social media platform, wherein said determination of said part of speech is based on a context database; categorizing, by said one or more processors, said each word of said plurality of words in one or more categories based on said part of speech associated with said each word; determining, by said one or more processors, context of said one or more conversations based on said categorization; determining, by said one or more processors, a third score associated with said user based on said context of said one or more conversations; determining, by said one or more processors, said psychological type of said user based on said first score, said second score, and said third score; and transmitting information, by said one or more processors, based on said determined psychological type, wherein said information indicates at least one of promotional offers, advertisements, marketing strategies, or publicity strategies. 2. The method of claim 1 , wherein said one or more categories are defined in said context database.
| 0.846626 |
7,630,778 | 9 | 10 |
9. The system of claim 1 wherein said first constraint set comprises a constraint selected from the group consisting of product aesthetic constraints, product promotion constraints, product packaging constraints, regulatory constraints, and combinations thereof.
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9. The system of claim 1 wherein said first constraint set comprises a constraint selected from the group consisting of product aesthetic constraints, product promotion constraints, product packaging constraints, regulatory constraints, and combinations thereof. 10. The system of claim 9 wherein said first constraint set comprises at Least two constraints selected from the group consisting of product aesthetic constraints, product promotion constraints, product packaging constraints, regulatory constraints, and combinations thereof.
| 0.5 |
8,923,630 | 1 | 5 |
1. A data mining method, comprising: receiving a set of multimodal data objects comprising semantically interrelated information of a first type and a second type, each being of a different type selected from the group consisting of image information, audio information, video information, and semantic information; representing at least the first type of information of the multimodal data objects as feature vectors within a feature space comprising the first type of information and the second type of information, and the semantic interrelation between the first type of information and the second type of information; clustering the feature vectors into classified clusters according to at least one semantic clustering criterion by at least one automated processor, to thereby determine a classification of the respective feature vectors; associating data objects with respective members of the set of multimodal data objects by the at least one automated processor, based on the clustering, the associated data objects comprising information of a third type semantically interrelated to the second type of information, selected from the group consisting of images, audio, video and semantic information, wherein the type of information of the third type is distinct from the type of information of the first type; estimating a joint feature representation of the set of multimodal data objects and the associated data objects by the at least one automated processor; optimizing the joint feature representation by the at least one automated processor to provide a structured output space of interdependent objects, based on at least a prediction error criterion, by iteratively solving a dual problem by selectively partitioning data objects into a working set and a non-working set, comprising: moving the data objects in the non-working set that can be moved without changing an objective function to the working set, and moving the data objects in the working set that can be moved with a decrease in the objective function to the non-working set; receiving a query represented according to the first type of information; and identifying data objects from the set of multimodal data objects that correspond to the query by the at least one automated processor, based on at least the structured output space of interdependent multimodal objects.
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1. A data mining method, comprising: receiving a set of multimodal data objects comprising semantically interrelated information of a first type and a second type, each being of a different type selected from the group consisting of image information, audio information, video information, and semantic information; representing at least the first type of information of the multimodal data objects as feature vectors within a feature space comprising the first type of information and the second type of information, and the semantic interrelation between the first type of information and the second type of information; clustering the feature vectors into classified clusters according to at least one semantic clustering criterion by at least one automated processor, to thereby determine a classification of the respective feature vectors; associating data objects with respective members of the set of multimodal data objects by the at least one automated processor, based on the clustering, the associated data objects comprising information of a third type semantically interrelated to the second type of information, selected from the group consisting of images, audio, video and semantic information, wherein the type of information of the third type is distinct from the type of information of the first type; estimating a joint feature representation of the set of multimodal data objects and the associated data objects by the at least one automated processor; optimizing the joint feature representation by the at least one automated processor to provide a structured output space of interdependent objects, based on at least a prediction error criterion, by iteratively solving a dual problem by selectively partitioning data objects into a working set and a non-working set, comprising: moving the data objects in the non-working set that can be moved without changing an objective function to the working set, and moving the data objects in the working set that can be moved with a decrease in the objective function to the non-working set; receiving a query represented according to the first type of information; and identifying data objects from the set of multimodal data objects that correspond to the query by the at least one automated processor, based on at least the structured output space of interdependent multimodal objects. 5. The method according to claim 1 , wherein the first type of information comprises semantic information and the second type of information comprises audio information.
| 0.913422 |
8,533,218 | 3 | 4 |
3. The debugger component of the data processing system of claim 1 , wherein the multidimensional database is sourced from a physical persistent system.
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3. The debugger component of the data processing system of claim 1 , wherein the multidimensional database is sourced from a physical persistent system. 4. The debugger component of the data processing system of claim 3 , wherein the physical persistent system is a relational database.
| 0.5 |
8,898,065 | 1 | 4 |
1. A method of performing speech recognition in a distributed system comprising an electronic device including an embedded speech recognizer and a network device including a remote speech recognizer remote from the electronic device, the method comprising: receiving, by the electronic device, input audio comprising speech; determining that at least a portion of the input audio matches a recognition grammar associated with the embedded speech recognizer; generating a search tree associated with the recognition grammar, wherein the search tree includes a plurality of nodes, wherein each of the nodes is associated with a type of item in the recognition grammar; determining whether the recognition grammar includes at least one generic speech nod, wherein determining whether the recognition grammar includes at least one generic speech node comprises determining whether the search tree includes only nodes associated with types of items that can be recognized by the embedded speech recognizer with an accuracy above a threshold; determining that recognition by the remote speech recognizer is desired in response to determining that the recognition grammar includes at least one generic speech node indicating that the speech in the input audio may include free-form dictation; and sending at least a portion of the input audio to the network device in response to determining that recognition by the remote speech recognizer is desired.
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1. A method of performing speech recognition in a distributed system comprising an electronic device including an embedded speech recognizer and a network device including a remote speech recognizer remote from the electronic device, the method comprising: receiving, by the electronic device, input audio comprising speech; determining that at least a portion of the input audio matches a recognition grammar associated with the embedded speech recognizer; generating a search tree associated with the recognition grammar, wherein the search tree includes a plurality of nodes, wherein each of the nodes is associated with a type of item in the recognition grammar; determining whether the recognition grammar includes at least one generic speech nod, wherein determining whether the recognition grammar includes at least one generic speech node comprises determining whether the search tree includes only nodes associated with types of items that can be recognized by the embedded speech recognizer with an accuracy above a threshold; determining that recognition by the remote speech recognizer is desired in response to determining that the recognition grammar includes at least one generic speech node indicating that the speech in the input audio may include free-form dictation; and sending at least a portion of the input audio to the network device in response to determining that recognition by the remote speech recognizer is desired. 4. The method of claim 1 , wherein determining that at least a portion of the input audio matches a recognition grammar comprises determining that the at least a portion of the input audio matches a voice command.
| 0.794402 |
9,691,169 | 29 | 31 |
29. One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising: receiving data representing a glyph in a font to present the glyph on a display; in response to operations being executed to present the glyph on the display, identifying one or more values shared by glyphs of the font for adjusting the appearance of the glyph, from a data table stored with the glyph in the font, either one or multiple instructions being executed based upon a comparison of adjusted versions of the glyph to identify the one or more shared values; and adjusting a representation of the glyph using the identified one or more shared values for presentation on the display.
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29. One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising: receiving data representing a glyph in a font to present the glyph on a display; in response to operations being executed to present the glyph on the display, identifying one or more values shared by glyphs of the font for adjusting the appearance of the glyph, from a data table stored with the glyph in the font, either one or multiple instructions being executed based upon a comparison of adjusted versions of the glyph to identify the one or more shared values; and adjusting a representation of the glyph using the identified one or more shared values for presentation on the display. 31. The non-transitory computer readable media of claim 29 , wherein the shared values associated with the font represent control values.
| 0.830446 |
9,122,760 | 1 | 4 |
1. A system for assisting users with the selection of items on the Internet, comprising: one or more hardware processors; at least one web robot operable on the one or more hardware processors for crawling multiple websites to determine published userIDs and associated published preferences for items that are available on the web; a database accessible to the one or more hardware processors for storing the userIDs and associated preferences; software operable on the one or more hardware processors for performing an analysis and suggestion function; wherein the system assumes until determined otherwise that a userID used by a first user on a first website represents the same user as the same userID used by a second user on a second website; wherein associated preferences stored for a particular userID include preferences for items available from a plurality of websites; wherein the system provides a third user with a suggested first item based on the expressed preferences of at least the first and second users across multiple websites relative to the first item and items that at least the first and second users have previously reviewed; wherein the suggested first item provided to the third user is based on both positive and negative preferences of the first and second users; wherein a weighting profile is created for weighting rating values that represent positive and negative preferences; and wherein the weighting profile is deployed by the system with respect to combining preferences of the first and second users in suggesting the first item.
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1. A system for assisting users with the selection of items on the Internet, comprising: one or more hardware processors; at least one web robot operable on the one or more hardware processors for crawling multiple websites to determine published userIDs and associated published preferences for items that are available on the web; a database accessible to the one or more hardware processors for storing the userIDs and associated preferences; software operable on the one or more hardware processors for performing an analysis and suggestion function; wherein the system assumes until determined otherwise that a userID used by a first user on a first website represents the same user as the same userID used by a second user on a second website; wherein associated preferences stored for a particular userID include preferences for items available from a plurality of websites; wherein the system provides a third user with a suggested first item based on the expressed preferences of at least the first and second users across multiple websites relative to the first item and items that at least the first and second users have previously reviewed; wherein the suggested first item provided to the third user is based on both positive and negative preferences of the first and second users; wherein a weighting profile is created for weighting rating values that represent positive and negative preferences; and wherein the weighting profile is deployed by the system with respect to combining preferences of the first and second users in suggesting the first item. 4. The system of claim 1 , wherein when the third user requests suggestions relative to a specific product or service category, providing suggestions for items shown on multiple websites based on preferences of users who had similar preferences to each other for items offered on multiple websites and who also had a specified level of preference for said specific product or service category; and wherein the third user need provide no preference information beyond requesting suggestions relative to the specific product or service category in order to receive the suggestions.
| 0.5 |
7,909,326 | 1 | 5 |
1. A method for producing a lottery product providing a story, the method comprising: printing a first page that embodies a first instant game, the first page including a first removable covering concealing a first element of a story, and the first page being associated with a first predetermined sub-payout, and the first page indicating a first predetermined running value of the lottery product; printing a second page that embodies a second instant game, the second page including a second removable covering concealing a second element of the story, and the second page being associated with a second predetermined sub-payout, and the second page indicating a second predetermined running value of the lottery product, the second predetermined running value being based on the first predetermined sub-payout and the second predetermined sub-payout; printing a table that (1) identifies a third element of the story and indicates a first potential prize for the first instant game if the third element matches the first element and (2) identifies a fourth element of the story and indicates a second potential prize for the second instant game if the fourth element matches the second element; and assembling the first page, the second page, and the table into a lottery product.
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1. A method for producing a lottery product providing a story, the method comprising: printing a first page that embodies a first instant game, the first page including a first removable covering concealing a first element of a story, and the first page being associated with a first predetermined sub-payout, and the first page indicating a first predetermined running value of the lottery product; printing a second page that embodies a second instant game, the second page including a second removable covering concealing a second element of the story, and the second page being associated with a second predetermined sub-payout, and the second page indicating a second predetermined running value of the lottery product, the second predetermined running value being based on the first predetermined sub-payout and the second predetermined sub-payout; printing a table that (1) identifies a third element of the story and indicates a first potential prize for the first instant game if the third element matches the first element and (2) identifies a fourth element of the story and indicates a second potential prize for the second instant game if the fourth element matches the second element; and assembling the first page, the second page, and the table into a lottery product. 5. The method of claim 1 , in which the first removable covering conceals a representation of at least one character in the story.
| 0.895833 |
8,566,079 | 7 | 10 |
7. An apparatus, comprising: one or more computer processors that execute: using an input sentence to extract an extracted example sentence from a set of example sentences according to a matching evaluation on a character block basis between the input sentence and the set of example sentences; selecting, as a reevaluation portion, a portion of the input sentence other than a portion that contributed to the matching evaluation for the extracting of the extracted example sentence; re-extracting another example sentence from the set of example sentences according to a re-evaluation of the matching using the reevaluation portion of the input sentence; and identifying example sentence segments for segments of the input sentence based upon candidate sentence segments according to the extracted and re-extracted example sentences.
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7. An apparatus, comprising: one or more computer processors that execute: using an input sentence to extract an extracted example sentence from a set of example sentences according to a matching evaluation on a character block basis between the input sentence and the set of example sentences; selecting, as a reevaluation portion, a portion of the input sentence other than a portion that contributed to the matching evaluation for the extracting of the extracted example sentence; re-extracting another example sentence from the set of example sentences according to a re-evaluation of the matching using the reevaluation portion of the input sentence; and identifying example sentence segments for segments of the input sentence based upon candidate sentence segments according to the extracted and re-extracted example sentences. 10. The apparatus according to claim 7 , wherein the matching evaluation includes evaluating degrees of matching on a character block basis between the input sentence and the set of example sentences.
| 0.621212 |
8,626,712 | 12 | 17 |
12. A computer-readable storage device having computer-executable instructions stored thereon, which when executed perform acts, comprising: for each of a set of data items relating to experiences of a human user of a computing device, enabling at least one processor to iteratively obtain and store values of a selected subset of the set of data items, each stored value of a data item being stored with an indication of the data item and an indication of an effective time of the stored value, at least one data item obtaining values from a plurality of data sources, the data sources comprising at least one of a source of geographic information and physiological information; enabling the at least one processor to receive, from at least one application that performs logged context attribute analysis, a specification for analyzing values among the stored values that specifies one or more data items, a range of effective times, and an analysis technique applicable to the data items, the analysis technique includes determining a result that would have been produced had a rule been applied to analyze the specified context attribute values at the time the values were generated, the rule configured for analyzing context attribute values in real-time to produce a result, the rule adopted for future real-time application when it is determined that a successful result would have been produced had the rule been applied to analyze the specified context attribute values at the time the values were generated; enabling the at least one processor to retrieve stored values for the specified data items within the specified range of effective times and retrieving the real time values for the remaining non-specified data items; enabling the at least one processor to apply the specified analysis technique to the retrieved values using the specified one or more context attributes to produce an analysis of experiences of the human user; and enabling the at least one processor to select an operating characteristic of the computing device based on inferring a current or future status of the human user based on the analysis of experiences of the human user.
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12. A computer-readable storage device having computer-executable instructions stored thereon, which when executed perform acts, comprising: for each of a set of data items relating to experiences of a human user of a computing device, enabling at least one processor to iteratively obtain and store values of a selected subset of the set of data items, each stored value of a data item being stored with an indication of the data item and an indication of an effective time of the stored value, at least one data item obtaining values from a plurality of data sources, the data sources comprising at least one of a source of geographic information and physiological information; enabling the at least one processor to receive, from at least one application that performs logged context attribute analysis, a specification for analyzing values among the stored values that specifies one or more data items, a range of effective times, and an analysis technique applicable to the data items, the analysis technique includes determining a result that would have been produced had a rule been applied to analyze the specified context attribute values at the time the values were generated, the rule configured for analyzing context attribute values in real-time to produce a result, the rule adopted for future real-time application when it is determined that a successful result would have been produced had the rule been applied to analyze the specified context attribute values at the time the values were generated; enabling the at least one processor to retrieve stored values for the specified data items within the specified range of effective times and retrieving the real time values for the remaining non-specified data items; enabling the at least one processor to apply the specified analysis technique to the retrieved values using the specified one or more context attributes to produce an analysis of experiences of the human user; and enabling the at least one processor to select an operating characteristic of the computing device based on inferring a current or future status of the human user based on the analysis of experiences of the human user. 17. The computer-readable storage device of claim 12 , further comprising, enabling the at least one processor to: receive a user specification of a user-selected mediation technique; and employ the user-selected mediation technique to select which one of the plurality of data sources will supply values for the analysis.
| 0.5 |
7,970,760 | 3 | 4 |
3. The method of claim 1 wherein generating a score for the plurality of ranked content items identified as responsive to the query comprises generating a score indicating a degree to which the plurality of ranked content items are responsive to the query.
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3. The method of claim 1 wherein generating a score for the plurality of ranked content items identified as responsive to the query comprises generating a score indicating a degree to which the plurality of ranked content items are responsive to the query. 4. The method of claim 3 wherein generating a score indicating a degree to which the plurality of ranked content items are responsive to the query comprises generating a score for a given content item based upon a degree to which plurality of ranking features of the content item are responsive to the query.
| 0.5 |
7,882,119 | 1 | 13 |
1. A document alignment method comprising: inputting source leaves of a source document in first tree structured format, the first tree structured format comprising nodes which are ultimately connected with the source leaves by paths, text content of the source document being distributed among the source leaves; inputting target leaves of a target document in second tree structured format, the second tree structured format comprising nodes which are ultimately connected with the target leaves by paths, text content of the target document being distributed among the target leaves; assigning a cost to each of a plurality of matches based on text content of the leaves, each match comprising elements selected from the group consisting of: a source leaf and a target leaf, an unmatched source leaf, and an unmatched target leaf; identifying a set of matches for which a total cost is minimal, wherein each of the input source and target leaves is in at least one of the identified matches; identifying, from the set of identified matches, groups of matches wherein each match in the group has a leaf in common; identifying, from the groups, probable matches in which more than one target leaf is matched with at least one source leaf and probable matches where more than one source leaf is matched with a target leaf; outputting an alignment between leaves of the target document and leaves of the source document which includes the probable matches.
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1. A document alignment method comprising: inputting source leaves of a source document in first tree structured format, the first tree structured format comprising nodes which are ultimately connected with the source leaves by paths, text content of the source document being distributed among the source leaves; inputting target leaves of a target document in second tree structured format, the second tree structured format comprising nodes which are ultimately connected with the target leaves by paths, text content of the target document being distributed among the target leaves; assigning a cost to each of a plurality of matches based on text content of the leaves, each match comprising elements selected from the group consisting of: a source leaf and a target leaf, an unmatched source leaf, and an unmatched target leaf; identifying a set of matches for which a total cost is minimal, wherein each of the input source and target leaves is in at least one of the identified matches; identifying, from the set of identified matches, groups of matches wherein each match in the group has a leaf in common; identifying, from the groups, probable matches in which more than one target leaf is matched with at least one source leaf and probable matches where more than one source leaf is matched with a target leaf; outputting an alignment between leaves of the target document and leaves of the source document which includes the probable matches. 13. The method of claim 1 , wherein the identifying of probable matches in which more than one target leaf is matched with at least one source leaf and probable matches where more than one source leaf is matched with a target leaf includes determining whether the group as a whole has a higher similarity than the elements from which the group is derived.
| 0.85415 |
9,652,445 | 9 | 10 |
9. The method of claim 8 , wherein each field in the set of fields in the one or more security groups is categorized in the one or more groups based on the semantic type of field in the set of fields.
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9. The method of claim 8 , wherein each field in the set of fields in the one or more security groups is categorized in the one or more groups based on the semantic type of field in the set of fields. 10. The method of claim 9 , further comprising creating a new group based on a sub-sematic type of at least a field in the first set of fields, when a number of fields in the first set of fields exceeds a predetermined threshold value.
| 0.5 |
7,966,408 | 5 | 18 |
5. The method according to claim 1 , further comprising: describing an association between the Adaptation Module and a MediaItems Module, represented by a link.
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5. The method according to claim 1 , further comprising: describing an association between the Adaptation Module and a MediaItems Module, represented by a link. 18. The method according to claim 5 , further comprising: describing the alternative media items of the MediaItems Module used in the Adaptation Module by media-specific information encompassing bandwidth and size of the visual portion of a multimedia presentation, meta information encompassing a name, genre, and actor of the alternative media items or Universal Resource Identifiers (URIs).
| 0.5 |
9,058,505 | 1 | 2 |
1. A method to control access to information, the method comprising: computer hardware determining whether a first type of field of a first document has restricted access; the computer hardware generating a modified list of index terms by encrypting tokens occurring in the first type of field using a first set of encryption settings; the computer hardware executing an indexing step using the modified list of index terms; the computer hardware generating a modified list of search terms by adding first additional search terms to a list of search terms, wherein the first additional terms include synonyms of the search terms and terms that are related to the search terms; the computer hardware removing frequently used words from the modified list of search terms; and responsive to a determination that a user has authorization to view the first type of field, the computer hardware adding to the modified list of search terms an encrypted version of a search term included in the list of search terms such that execution of a search using the modified list of search terms returns a result that identifies the first document as a search result when either an unencrypted or an encrypted version of a search term is found in the index terms associated with the first document.
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1. A method to control access to information, the method comprising: computer hardware determining whether a first type of field of a first document has restricted access; the computer hardware generating a modified list of index terms by encrypting tokens occurring in the first type of field using a first set of encryption settings; the computer hardware executing an indexing step using the modified list of index terms; the computer hardware generating a modified list of search terms by adding first additional search terms to a list of search terms, wherein the first additional terms include synonyms of the search terms and terms that are related to the search terms; the computer hardware removing frequently used words from the modified list of search terms; and responsive to a determination that a user has authorization to view the first type of field, the computer hardware adding to the modified list of search terms an encrypted version of a search term included in the list of search terms such that execution of a search using the modified list of search terms returns a result that identifies the first document as a search result when either an unencrypted or an encrypted version of a search term is found in the index terms associated with the first document. 2. The method of claim 1 , the method further including: the computer hardware determining whether the user has authorization to view the first type of field, based on a first degree of authorization of the user; the computer hardware generating the modified list of search terms by adding second additional search terms to a list of search terms, based on the first degree of authorization of the user to view the first type of field, wherein the second additional search terms are encrypted search terms created using the first set of encryption settings; the computer hardware executing a search using the modified list of search terms; and the computer hardware identifying a search result based, at least in part, on the modified list of search terms.
| 0.5 |
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