System for semantically disambiguating text information
First Claim
1. An ontology engine, comprising:
- a storage holding a vocabulary, the vocabulary including a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
an input interface unit that accepts text information, selects those machine-readable IDs whose keywords match up with the text information, and returns a list of candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description;
a human interface unit that allows a user to select one of the candidates; and
an output interface unit that returns one of the machine-readable IDs corresponding to the candidate selected at the human interface.
1 Assignment
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Accused Products
Abstract
Disclosed is a semantic user interface system that allows text information to be tagged with machine-readable IDs that are associated with concepts for conveying information without any ambiguity or without being hampered by the limitations of human languages. Typically, a plurality of vocabularies are stored across a network, and each vocabulary includes a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID. An input interface accepts text information, selects those machine-readable IDs whose keywords match up with the text information, and returns a list of candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description. The machine-readable IDs can carry information in the form of concepts without any ambiguity as opposed to text information. This system can be applied to web and database searches, publishing messages to selected subscribers, interfacing of applications software, machine translations, etc.
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Citations
58 Claims
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1. An ontology engine, comprising:
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a storage holding a vocabulary, the vocabulary including a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
an input interface unit that accepts text information, selects those machine-readable IDs whose keywords match up with the text information, and returns a list of candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description;
a human interface unit that allows a user to select one of the candidates; and
an output interface unit that returns one of the machine-readable IDs corresponding to the candidate selected at the human interface. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. An ontology engine, comprising:
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a storage holding a vocabulary, the vocabulary including a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
an input interface unit that accepts a machine-readable ID; and
an output interface unit that returns at least one of the keywords corresponding to each accepted machine-readable ID. - View Dependent Claims (22, 23, 24, 25)
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26. A ontology engine, comprising:
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a storage holding a vocabulary, the vocabulary including a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID, the concepts being at least partly linked to each other on the basis of a parent-child relationship;
an input interface unit that accepts a machine-readable ID; and
an output interface unit that returns another machine-readable ID corresponding to a concept that is a parent or child to the concept corresponding to each accepted machine-readable ID. - View Dependent Claims (27, 28)
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29. A ontology engine, comprising:
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a storage holding a plurality of discrete vocabularies, each vocabulary including a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID, at least some of the concepts in the different vocabularies being linked to each other on the basis of a prescribed relationship;
an input interface unit that accepts a machine-readable ID from a first one of the discrete vocabularies; and
an output interface unit that returns another machine-readable ID corresponding to a concept belonging to a second one of the discrete vocabularies that is related to the concept corresponding to each accepted machine-readable ID.
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30. An input method for semantically tagging entered text information, comprising:
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mounting a vocabulary that includes a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
entering text information;
matching the entered text information with the keywords that are held in the vocabulary and returning a list of candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description;
allowing selection of one of the candidates; and
returning the machine-readable ID corresponding to the selected candidate.
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31. An output method for disambiguating text information by detecting a tag attached to the text information, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
extracting a machine-readable ID from text information; and
returning at least one of the keywords corresponding to the extracted machine-readable ID by looking up the vocabulary. - View Dependent Claims (32)
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33. A file save method using an ontology engine, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
providing a file save dialog that allows text information describing the file to be entered;
matching the text information with the keywords in the vocabulary and extracting corresponding machine-readable IDs from the vocabulary;
listing candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description;
allowing a user to select one of the candidates; and
tagging the file with the machine-readable ID corresponding to the selected candidate before saving the file.
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34. A file save method using an ontology engine, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
providing a file save dialog that indicates a directory in which a file is going to be saved and allows text information describing the file to be entered;
matching the text information with the keywords in the vocabulary and extracting corresponding machine-readable IDs from the vocabulary;
listing candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description;
allowing a user to select one of the candidates; and
tagging the file with the machine-readable ID corresponding to the selected candidate before saving the file.
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35. A method of allocating a file that is tagged with a machine-readable ID corresponding to a concept to a virtual directory according to the concept by using an ontology engine, comprising:
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creating a plurality of virtual directories each represented by a concept; and
allocating a file to at least one of the virtual directories according to a machine-readable ID that is tagged to the file and matches the concept represented by the at least one of the virtual directories. - View Dependent Claims (36, 37, 38, 39)
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40. A file search method using an ontology engine, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
entering text information that describes a desired file;
matching the text information with the keywords in the vocabulary and extracting corresponding machine-readable IDs from the vocabulary;
listing candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description;
allowing a user to select one of the candidates; and
searching a file that is tagged with a machine-readable ID corresponding to the selected candidate. - View Dependent Claims (41, 42, 43, 44, 45, 46, 47)
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48. A method of accepting a command in application software, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to a command for the application software and at least one keyword corresponding to each command;
entering text information that describes a desired command;
matching the text information with the keywords in the vocabulary and extracting corresponding commands from the vocabulary;
listing candidates each corresponding to one of the extracted commands and including a corresponding description;
allowing a user to select one of the candidates; and
forwarding a command that corresponds to the selected candidate for execution in the application software. - View Dependent Claims (49, 50)
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51. A method of embedding a machine-readable ID along with text information in a document so as to serve as a command in an application software, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to certain specific data for the application software and at least one keyword corresponding to each specific data;
entering text information that describes desired command;
matching the text information with the keywords in the vocabulary and extracting a corresponding machine-readable ID from the vocabulary; and
forwarding the extracted machine-readable ID to be stored in the document.
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52. A method of embedding a machine-readable ID along with text information in a document so as to serve as input data for a command in an application software, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to certain specific data for the application software and at least one keyword corresponding to each specific data;
entering text information that describes desired data;
matching the text information with the keywords in the vocabulary and extracting a corresponding machine-readable ID from the vocabulary; and
forwarding the extracted machine-readable ID to be stored in the document.
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53. A method of publishing a plurality of messages so as to selectively deliver the messages to each of a plurality of subscribers by taking into account a predetermined preference of the subscriber, comprising:
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mounting a vocabulary that holds a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID;
allowing each subscriber to enter text information that represents a preference of the subscriber;
assigning at least one of the machine-readable IDs to the subscriber that is extracted from the vocabulary by matching the entered text information with the keywords;
assigning at least one machine-readable ID to each published message according to a concept that represents contents and/or attributes of the message;
finding matches between the machine-readable IDs assigned to the subscribers and the machine-readable IDs assigned to the messages; and
delivering each message only to those subscribers whose machine-readable ID matches with the machine-readable ID of the message. - View Dependent Claims (54, 55, 56, 57, 58)
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Specification