Ontomerge: A system for merging DL-Lite ontologies
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Wang, K
Jin, Y
Qi, G
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Abstract
Merging multi-sourced ontologies in a consistent manner is an important and challenging research topic. In this paper, we propose a novel approach for merging DL-LiteN bool ontologies by adapting the classical model-based belief merging approach, where the minimality of changes is realised via a semantic notion, model distance. Instead of using classical DL models, which may be infinite structures in general, we define our merging operator based on a new semantic characterisation for DL-Lite. We show that subclass relation w.r.t. the result of merging can be checked efficiently via a QBF reduction. We present our system OntoMerge, which effectively answers subclass queries on the resulting ontology of merging, without first computing the merging results. Our system can be used for answering subclass queries on multiple ontologies.
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CEUR Workshop Proceedings
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969
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© The Author(s) 2012. 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 author[s].
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Artificial intelligence not elsewhere classified
Information systems