arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1711.03430cs.AI
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Repairing Ontologies via Axiom Weakening

KRDB, Unibz, Bozen-Bolzano(博尔扎诺自由大学 KRDB 中心)

Nicolas Troquard, Roberto Confalonieri, Pietro Galliani, Rafael Penaloza, Daniele Porello, Oliver Kutz

英文摘要:

Ontology engineering is a hard and error-prone task, in which small changes may lead to errors, or even produce an inconsistent ontology. As ontologies grow in size, the need for automated methods for repairing inconsistencies while preserving as much of the original knowledge as possible increases. Most previous approaches to this task are based on removing a few axioms from the ontology to regain consistency. We propose a new method based on weakening these axioms to make them less restrictive, employing the use of refinement operators. We introduce the theoretical framework for weakening DL ontologies, propose algorithms to repair ontologies based on the framework, and provide an analysis of the computational complexity. Through an empirical analysis made over real-life ontologies, we show that our approach preserves significantly more of the original knowledge of the ontology than removing axioms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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