Data integration systems attempt to provide users with seamless and flexible access to information from multiple autonomous, distributed and heterogeneous data sources through a unified query interface. Besides data are continuously growing, maintained by different organizations and managed autonomously, querying data from heterogeneous data sources faces new challenges. As data integration has been automated, the ambiguity in concept interpretation also known as semantic heterogeneity has become one of the main obstacles to this process. Introduction of the Semantic Web Vision [5] and the shift towards machine-understandable web resources have underscored the importance of automatic semantic integration of data elements. Ontologies[7] have been widely accepted as the model of choice for modeling heterogeneous data sources by various communities including the areas of databases, Knowledge representation and Information retrieval. WordNet ontology[3] is a large lexical database that is used in many schema matching algorithms to match schemas based on the semantics of attributes. In this paper ontology based semantic query reformulation technique is followed to improve the recall of the query. The reformulated query is optimized by removing disjunctive clauses in the query to reduce the computational cost of the semantic query execution. Experimental results show that the proposed optimization technique improves recall with minimal execution time
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