Semantically intelligent semi-automated ontology integration

An ontology is a way of information categorization and storage. Web Ontologies provide help in retrieving the required and precise information over the web. However, the problem of heterogeneity between ontologies may occur in the use of multiple ontologies of the same domain. The integration of ontologies provides a solution for the heterogeneity problem. Ontology integration is a solution to problem of interoperability in the knowledge based systems. Ontology integration provides a mechanism to find the semantic association between a pair of reference ontologies based on their concepts. Many researchers have been working on the problem of ontology integration; however, multiple issues related to ontology integration are still not addressed. This dissertation involves the investigation of the ontology integration problem and proposes a layer based enhanced framework as a solution to the problem. The comparison between concepts of reference ontologies is based on their semantics along with their syntax in the concept matching process of ontology integration. The semantic relationship of a concept with other concepts between ontologies and the provision of user confirmation (only for the problematic cases) are also taken into account in this process. The proposed framework is implemented and validated by providing a comparison of the proposed concept matching technique with the existing techniques. The test case scenarios are provided in order to compare and analyse the proposed framework in the analysis phase. The results of the experiments completed demonstrate the efficacy and success of the proposed framework