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ConSim: an enhanced semantic similarity measure to find the relationship between concepts in cross ontology

Ontology has become the key concept for providing relevant and accurate information to the users for a particular domain or from multiple domains. To extract similar concepts from multiple ontologies, there is a need to develop a concept similarity measure between two independent ontologies. The intention of finding semantic similarity is to enhance the integration and retrieval of resources in a more meaningful and accurate way. Based on the existing hybrid similarity measures an enhanced similarity measure is proposed which brings out a more accurate relationship between the two concepts of different ontologies, the proposed measure is equivalent to human judgments. The proposed method has an improved technique over other methods. The experimental results establish the efficiency of our proposed work and reveals that similarity measure for cross ontology out performs the current hybrid similarity measures by 20% in terms of correlation coefficients.