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AAAI 2017

Ontology Materialization by Abstraction Refinement in Horn SHOIF

Conference Paper AAAI Technical Track: Knowledge Representation and Reasoning Artificial Intelligence

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 equalitymaterialization. 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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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
1051395171474995336