An Ontology Matching Approach Based on Affinity-Preserving Random Walks

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 graphbased 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, AffinityPreserving Random Walk (APRW) and MappingOriented 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.