Considerable research in the field of ontology matching has been performed where information sharingand reuse becomes necessary in ontology development. Measurement of lexical similarity in ontologymatching is performed using synset, defined in WordNet. In this paper, we defined a Super Word Set,which is an aggregate set that includes hypernym, hyponym, holonym, and meronym sets in WordNet.The Super Word Set Similarity is calculated by the rate of words of concept name and synset’s wordsinclusion in the Super Word Set. In order to measure of Super Word Set Similarity, we first extractedMatched Concepts(MC), Matched Properties(MP) and Property Unmatched Concepts(PUC) from theresult of ontology matching. We compared these against two ontology matching tools – COMA++ andLOM. The Super Word Set Similarity shows an average improvement of 12% over COMA++ and 19%over LOM.