Learning complex mappings between ontologies

Authors:
Wei Hu;Jianfeng Chen;Hang Zhang;Yuzhong Qu
Affiliations:
State Key Laboratory for Novel Software Technology, Nanjing University, China;State Key Laboratory for Novel Software Technology, Nanjing University, China;State Key Laboratory for Novel Software Technology, Nanjing University, China;State Key Laboratory for Novel Software Technology, Nanjing University, China
Venue:
JIST'11 Proceedings of the 2011 joint international conference on The Semantic Web
Year:
2011

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Abstract

In this paper, we introduce a new approach for constructing complex mappings between ontologies by transforming it to a rule learning process. Derived from the classical Inductive Logic Programming, our approach uses instance mappings as training data and employs tailoring heuristics to improve the learning efficiency. Empirical evaluation shows that our generated Horn-rule mappings are meaningful.