DefinePK

Abstract

Increase in web and information technologies has made available to large number of independently created and managed information systems. These systems include similar information from disparate sources cause information heterogeneity. To achieve interoperability between heterogeneous information systems and unified integration of those systems heterogeneities between information systems needs to be reduced. Mostly information heterogeneity occurs in three levels: syntactic, structural and semantic. The semantic heterogeneity issue is not completely addressed yet. In this research syntactic, structural, data and semantic heterogeneities between information systems is considered and a novel ontology mapping technique is developed to resolve semantic heterogeneity achieving semantic interoperability between ontologies. Background knowledge has been taken as reference ontology as a part of this work. The Ontology Mapping For Information Management (OMFIM) algorithm is evaluated with OAEI (Ontology alignment Evaluation Initiative) benchmark dataset and the performance is compared against S-match algorithm. Result shows that our proposed method outperforms the S-match algorithm for solving semantic heterogeneity and also best suitable for the systems with insufficient lexical overlap and poor structural correspondence.