Instance-Based Ontology Matching with Rough Set Features Selection

Abstract

Ontologies are widely used in various domain such as medical, e-commerce and semantic web. However, heterogeneous ontologies are one of the main challenges in realizing the semantic interoperation in the domain of ontology. Ontology matching is proposed as the solution to realize the semantic interoperation. In general, three main categories of ontology matching strategies proposed by researchers: string based matching; structural based matching and also instance-based matching. Instances in ontology contain lot of semantic information which can be used for the matching purposes. However, some of the ontology contains superfluous concepts/classes which should be removed in order to increase the performance of matching. In this paper, an idea for instance-based matching with rough set feature selection capability approach is proposed to perform the ontology matching task and further increase the matching's efficiency is presented.