|An ontology matching approach based on affinity-preserving random walks
|Key Laboratory of Computational Linguistics, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Collaborative Innovation Center for Language Ability, Xuzhou, China
|24th International Joint Conference on Artificial Intelligence, IJCAI 2015
|24th International Joint Conference on Artificial Intelligence, IJCAI 2015.Buenos Aires, Argentina,2015/1/1,2015-January(1471-1478).
|Ontology matching is the process of finding semantic correspondences between entities from different ontologies. As an effective solution to linking different heterogeneous ontologies, ontology matching has attracted considerable attentions in recent years. In this paper, we propose a novel graph-based approach to ontology matching problem. Different from previous work, we formulate ontology matching as a random walk process on the association graph constructed from the to-be-matched ontologies. In particular, two variants of the conventional random walk process, namely, Affinity-Preserving Random Walk (APRW) and Mapping-Oriented Random Walk (MORW), have been proposed to alleviate the adverse effect of the falsemapping nodes in the association graph and to incorporate the 1-to-1 matching constraints presumed in ontology matching, respectively. Experiments on the Ontology Alignment Evaluation Initiative (OAEI1) datasets show that our approach achieves a competitive performance when compared with state-of-the-art systems, even though our approach does not utilize any external resources.
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