Ontology matching is one of the most important challenges in the semantic web. It is a technique which is used to find the semantic correspondences between entities which are modeled in different ontologies. Despite many research efforts in ontology matching, the matching process still suffers from severe problems with respect to the quality of the matching results. Furthermore, finding the correspondences, for the most part, is very time-consuming. In this paper, we examine how a pre-processing phase can improve the results of the matching process. A pre-processing phase is added to the matchers for the analysis of input ontologies so as to detect some inappropriate patterns which are modeled by various developers. Then, refactoring operations are utilized on detected patterns for achieving assimilated ontologies. Finally, our proposed approach is tested by ASMOV (Automated Semantic Matching of Ontologies with Verification), which is one of the top matchers in OAEI (Ontology Alignment Evaluation Initiative). Experimental results show that ontologies achieved from this proposed approach are more efficient than the original unrepaired ones, with respect to standard evaluation measures.

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