Several challenges to the field of ontology matching have been outlined in recent research. Among them, selection of the appropriate similarity measures as well as configuration tuning of their combination are known as fundamental issues that the community should deal with. In addition, verifying the semantic coherence of the discovered alignment is also known as a crucial task. Furthermore, the problem of semantic verification becomes harder in large scale ontology matching because almost all reasoning systems fail or cannot completely classify large ontologies. Because the challenging issues are both in basic matching techniques and in their combination, our approach is aimed to provide improvement at basic matcher level and at the level of framework as well. In this paper, we describe our YAM++ approach for solving these issues. We evaluated the efficiency of YAM++ in various OAEI2012 tracks. YAM++ is now one of the best ontology matching systems as measured in terms of F-measure. Most notably, the current version of YAM++