Ontology Discovery System Iterative Refinement
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Solution Overview
Problem
Current methods for generating ontologies from text are inefficient in determining meaningful relationships between nouns, particularly in handling polysemous nouns and missing contextual information.
Innovation Solution
A method and system that receive a set of words comprising verbs and nouns, determine ontological relationships based on associations with verbs and glosses, and use statistical processing to generate and modify ontological relationships, incorporating user feedback and external linguistic resources like WordNet.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to generate ontologies from text, then the process is simpler, but the accuracy of determining ontological relationships between nouns deteriorates
Solution Approach 1:
The patent segments the ontology generation process into multiple iterative stages: initial relationship determination based on verb-noun associations, statistical analysis of textual data, user feedback collection, and refinement cycles. Each stage processes specific aspects of relationship determination independently, improving overall accuracy without overwhelming system complexity.
Solution Approach 2:
The patent implements feedback mechanisms where user input and statistical analysis results are fed back into the ontology generation process. User feedback on determined relationships and statistical patterns from textual data continuously refine the ontological relationships, progressively improving measurement precision through iterative refinement.
2Measurement precision
If statistical processing and iterative refinement are implemented, then the accuracy of ontological relationships improves, but the processing time increases
Solution Approach 1:
The patent employs periodic action through iterative refinement cycles where the ontology generation process operates in repeated stages: initial determination, statistical analysis, feedback collection, and refinement. Each cycle improves accuracy progressively, allowing the system to balance processing time and precision by performing intensive analysis only when needed rather than continuously.
Solution Approach 2:
The patent performs preliminary statistical analysis of textual data and pre-processing of verb-noun associations before the main ontology generation. This preliminary action prepares data structures and identifies patterns in advance, reducing the computational burden during iterative refinement and minimizing overall processing time while maintaining accuracy improvements.
3Measurement precision
If user feedback is incorporated into the process, then the relevance of ontological relationships improves, but the ease of operation deteriorates
Solution Approach 1:
The patent implements structured feedback mechanisms where users provide input on determined ontological relationships through standardized interfaces. The system processes this feedback automatically and integrates it into the refinement process, improving relevance while maintaining ease of operation through automated processing of user input rather than requiring manual intervention in complex analysis tasks.
Solution Approach 2:
The patent enables the system to automatically process and utilize user feedback without requiring users to manually perform complex ontology analysis tasks. The system self-manages the integration of feedback into relationship refinement, performing statistical analysis and relationship determination automatically while users simply provide directional guidance, thus maintaining ease of operation while improving relevance.
Data Source
AI summary
Disclosed methods and systems are directed to generating ontological relationships. The methods and systems may include receiving a set of words comprising one or more verbs and a plurality of nouns and determining one or more first ontological relationships between the plurality of nouns based on an association of each of the nouns with at least one of the one or more verbs; and a correspondence between one or more glosses associated with each of the plurality of nouns. The methods and systems may include receiving an input associated with the one or more first ontological relationships, and determining, based on the input, one or more second ontological relationships between the plurality of nouns.