Most previous research on ontology integration has focused on similarity measure-ments between ontologicalentities, e.g.,lexicons,instances,schemasandtaxonomies, resultingin high computational costs of considering all possible pairs between two given ontologies. Inthis paper, we propose a novel approach to reducing computational complexity in ontology in-tegration. Thereby, we address theimportanceandtypes of concepts, for priority matching anddirect matching between concepts, respectively.Identity-based similarityis computed, to avoidcomparisons of all properties related to each concept, while matching between concepts. Theproblem of conflict in ontology integration has initially been explored on theinstance-levelandconcept-level. This is useful to avoid many cases of mismatching.