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Computing Best Ontology Excerpts via Weighted Partial Max-SAT Solving

 
: Chen, Jieying; Ma, Yue; Walther, Dirk

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Fulltext (PDF; )

Ortiz, M.:
31st International Workshop on Description Logics, DL 2018. Proceedings. Online resource : Co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018), Tempe, Arizona, US, October 27th to 29th, 2018
Tempe/Ariz., 2018 (CEUR Workshop Proceedings 2211)
http://ceur-ws.org/Vol-2211/
Paper 13, 12 pp.
International Workshop on Description Logics (DL) <31, 2018, Tempe/Ariz.>
International Conference on Principles of Knowledge Representation and Reasoning (KR) <16, 2018, Tempe/Ariz.>
English
Conference Paper, Electronic Publication
Fraunhofer IVI ()
ontologies; ontology excerpt

Abstract
We consider the problem of computing best excerpts of ontologies, which are selections of a certain, small number k of axioms that best capture the knowledge regarding a given set of weighted terms. Such excerpts can be useful for ontology selection, for instance. The weights of terms are to reflect different importances of considered terms, for which we propose an incompleteness measure of excerpts based on the term weights and the notion of logical difference. We present a method to compute best k-excerpts by finding all subsumption justifications and solving a weighted partial Max-SAT problem. We demonstrate the viability of our approach with an evaluation on biomedical ontologies.

: http://publica.fraunhofer.de/documents/N-535042.html