4.2 Article

Markov network based ontology matching

期刊

JOURNAL OF COMPUTER AND SYSTEM SCIENCES
卷 78, 期 1, 页码 105-118

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcss.2011.02.014

关键词

Ontology matching; Probabilistic reasoning; Markov networks

资金

  1. IMG4 consortium of the Israel Ministry of Trade and Industry
  2. Lynn and William Frankel Center for Computer Science

向作者/读者索取更多资源

Ontology matching is a vital step whenever there is a need to integrate and reason about overlapping domains of knowledge. Systems that automate this task are of a great need. iMatch is a probabilistic scheme for ontology matching based on Markov networks, which has several advantages over other probabilistic schemes. First, it handles the high computational complexity by doing approximate reasoning, rather then by ad-hoc pruning. Second, the probabilities that it uses are learned from matched data. Finally, iMatch naturally supports interactive semi-automatic matches. Experiments using the standard benchmark tests that compare our approach with the most promising existing systems show that iMatch is one of the top performers. (C) 2011 Published by Elsevier Inc.

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