IOnto - ontology driven approach for selecting appropriate ontology matching algorithm

Globalization allows many industries and enterprises to corporate and communicate with each other to provide services. In the era of knowledge management semantic web and related technology plays a major role. Ontology being the basic unit of semantic web realization will contain knowledge which is sharable between different domains. Ontology matching techniques are vital in querying and finding the knowledge in these. The problem arises when industries runs on different domains need to communicate with each other. Identifying the extent to which the knowledge is available in an ontology, with respect to a particular domain is a major problem. Currently this is done by human. Since there is no automated system one has to manually select an appropriate matching system and manually input the two ontology to be matched. This research addresses this issue by providing an efficient way of identifying the percentages of domain knowledge certain ontology has. The appropriate matching system will be then selected. This is an application research which uses the waterfall software development methodology. Once data is gathered, algorithms were designed, implemented and tested. System was developed using Java related technology using Jena as the inference engine. Test results provides a 67.7% of accuracy. This research will accelerate the enormous growth in the context of automatic communicating among different businesses which leads towards the concept of a global, single system for all businesses and industries.