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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.

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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.

Keywords:
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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.