Ontology matching (or mapping)--finding correspondences between semantically related entities of heterogeneous ontologies--becomes crucial for interoperability in distributed and intelligent environments. Although some efforts in ontology mapping have already been carried out, the issues of semantic heterogeneity and expert-interaction in a mapping process still need to be considered. Our intuition on these issues is inadequate semantics and unstructured taxonomies in ontologies. In order to overcome these obstacles, we propose a semantically enriched model of ontologies (called MetaOntoModel) where the semantics of concepts are enriched by adding domain independent knowledge (called meta-knowledge) based on three philosophical notions: identity, rigidity, and dependency. Our novel idea is if two concepts possess different kinds of meta-knowledge, then they are not possible to be matched. Thus, a direct concept matching is driven between the same meta-knowledge groups of two heterogen...