Ontology Materialization by Abstraction Refinement in Horn SHOIF

No. 1: Thirty-First AAAI Conference On Artificial Intelligence

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 31

AAAI Technical Track: Knowledge Representation and Reasoning

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.

10.1609/aaai.v31i1.10691