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Discovery of Emerging Design Patterns in Ontologies Using Tree Mining.
Agnieszka Ławrynowicz1, Jedrzej Potoniec1, Michał Robaczyk1
1Faculty of Computing, Poznan University of Technology, ul. Piotrowo 3, 60-965 Poznan, Poland.
Semantic Web
|December 4, 2018
Summary
This study introduces a novel tree-mining method to automatically discover emerging ontology design patterns. The approach identifies recurring axiom patterns, offering insights into ontology development and potential new design solutions.
Area of Science:
- Computer Science
- Artificial Intelligence
- Bioinformatics
Background:
- Ontologies are crucial for knowledge representation in various domains.
- Identifying recurring modeling patterns, or ontology design patterns, aids in developing robust and reusable ontologies.
- Existing methods for discovering these patterns are often manual and time-consuming.
Purpose of the Study:
- To develop and evaluate an automated method for discovering emerging ontology design patterns.
- To investigate the prevalence and characteristics of recurring axiom patterns within a large ontology corpus.
Main Methods:
- A two-step tree-mining approach was employed.
- Ontology axioms were transformed into a tree structure to identify axiom patterns.
- Association analysis was used to mine co-occurring axiom patterns for emerging design patterns.
Main Results:
- Recurring axiom patterns were found across individual ontologies and the entire dataset.
- Frequent, non-trivial patterns, some with millions of occurrences, were identified.
- The method successfully detected known ontology design pattern fragments, validating its effectiveness.
Conclusions:
- The proposed tree-mining method enables the automatic discovery of emerging ontology design patterns.
- This approach can be applied to arbitrary ontology sets, facilitating the identification of new design patterns.
- The findings contribute to more efficient and standardized ontology engineering practices.
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