Ontology Materialization by Abstraction Refinement in Horn SHOIF

Authors

  • Birte Glimm University of Ulm
  • Yevgeny Kazakov University of Ulm
  • Trung-Kien Tran University of Ulm

DOI:

https://doi.org/10.1609/aaai.v31i1.10691

Keywords:

Ontology materialization, Abstraction refinement, Ontology reasoning

Abstract

Abstraction refinement is a recently introduced technique using which reasoning over large ABoxes is reduced to reasoning over small abstract ABoxes. Although the approach is sound for any classical Description Logic such as SROIQ, it is complete only for Horn ALCHOI. In this paper, we propose an extension of this method that is now complete for Horn SHOIF and also handles role- and equality-materialization. To show completeness, we use a tailored set of materialization rules that loosely decouple the ABox from the TBox. An empirical evaluation demonstrates that, despite the new features, the abstractions are still significantly smaller than the original ontologies and the materialization can be computed efficiently.

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Published

2017-02-12

How to Cite

Glimm, B., Kazakov, Y., & Tran, T.-K. (2017). Ontology Materialization by Abstraction Refinement in Horn SHOIF. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.10691

Issue

Section

AAAI Technical Track: Knowledge Representation and Reasoning