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The definition of new concepts or roles for which extensional knowledge become available can turn out to be necessary to make a DL ontology evolve. In this paper we reformulate this task as a machine learning problem and study a solution based on techniques borrowed from that form of logic-based machine learning known under the name of Inductive Logic Programming (ILP). More precisely, we propose to adapt previous ILP results to the knowledge representation framework of DL+log in order to learn rules to be used for changing SHIQ ontologies.dblp:conf/swap/LisiE08 fatcat:wjnbiuqqnzgpvfp42acp2llfai