Rational Elimination of DL-Lite TBox Axioms
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Author(s)
Zhuang, Z
Wang, Z
Wang, K
Antoniou, G
Year published
2014
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An essential task in managing description logic (DL) ontologies is the elimination of problematic axioms. Such elimination is formalised as the operation of contraction in belief change. In this paper, we investigate contraction over DL-LiteR TBoxes. In belief change, a well known approach for defining contraction is via epistemic entrenchments which are preference orderings over formulas. The approach however is not applicable in DL-LiteR as classic belief change assumes an underlying logic that is different from DL-LiteR. Thus we reformulate the epistemic entrenchment approach to make it applicable to DL-LiteR. We then ...
View more >An essential task in managing description logic (DL) ontologies is the elimination of problematic axioms. Such elimination is formalised as the operation of contraction in belief change. In this paper, we investigate contraction over DL-LiteR TBoxes. In belief change, a well known approach for defining contraction is via epistemic entrenchments which are preference orderings over formulas. The approach however is not applicable in DL-LiteR as classic belief change assumes an underlying logic that is different from DL-LiteR. Thus we reformulate the epistemic entrenchment approach to make it applicable to DL-LiteR. We then provide instantiation for the reformulated approach.
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View more >An essential task in managing description logic (DL) ontologies is the elimination of problematic axioms. Such elimination is formalised as the operation of contraction in belief change. In this paper, we investigate contraction over DL-LiteR TBoxes. In belief change, a well known approach for defining contraction is via epistemic entrenchments which are preference orderings over formulas. The approach however is not applicable in DL-LiteR as classic belief change assumes an underlying logic that is different from DL-LiteR. Thus we reformulate the epistemic entrenchment approach to make it applicable to DL-LiteR. We then provide instantiation for the reformulated approach.
View less >
Conference Title
CEUR Workshop Proceedings
Volume
1193
Publisher URI
Copyright Statement
© The Author(s) 2014. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference’s website or contact the authors.
Subject
Artificial intelligence not elsewhere classified
Information systems