Approximating Model-Based ABox Revision in DL-Lite: Theory and Practice

Authors

  • Guilin Qi Southeast University
  • Zhe Wang Griffith University
  • Kewen Wang Griffith University
  • Xuefeng Fu Southeast University
  • Zhiqiang Zhuang Griffith University

DOI:

https://doi.org/10.1609/aaai.v29i1.9200

Keywords:

Belief revision, Description logics, Ontology Evolution

Abstract

Model-based approaches provide a semantically well justified way to revise ontologies. However, in general, model-based revision operators are limited due to lack of efficient algorithms and inexpressibility of the revision results. In this paper, we make both theoretical and practical contribution to efficient computation of model-based revisions in DL-Lite. Specifically, we show that maximal approximations of two well-known model-based revisions for DL-Lite_R can be computed using a syntactic algorithm. However, such a coincidence of model-based and syntactic approaches does not hold when role functionality axioms are allowed. As a result, we identify conditions that guarantee such a coincidence for DL-Lite_FR. Our result shows that both model-based and syntactic revisions can co-exist seamlessly and the advantages of both approaches can be taken in one revision operator. Based on our theoretical results, we develop a graph-based algorithm for the revision operat

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Published

2015-02-09

How to Cite

Qi, G., Wang, Z., Wang, K., Fu, X., & Zhuang, Z. (2015). Approximating Model-Based ABox Revision in DL-Lite: Theory and Practice. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9200