A cluster based multiple ontology parallel merge method

Ontologies are an inevitable aspect of knowledge representation, processing, sharing and reuse and this in itself is the essence and significance of ontology. The number of ontologies available online is growing at a rapid pace. This conspicuous growth of ontologies enables sharing of knowledge in distributed and heterogeneous systems. The tremendous growth of ontologies has implied the popping up of multiple ontologies of the same domain. Applications developed based on these ontologies cannot achieve interoperability. To conquer this problem one of the optimum solution is to merge the ontologies in to a single general complete ontology. This brings up the need for a method which merges multiple ontologies, producing consistent, complete ontology. Another decisive factor worth consideration is the performance of multiple ontology merge process in terms of time. The current research work proposes a new cluster based multiple ontology parallel merge process. The performance of the multiple ontology merge process is fine-tuned by considering the similarity measure and parallel merge process. The proposed method produces consistent, optimum and complete knowledge of the domain as a single ontology with reduced time, which can be used by heterogeneous applications. The proposed method is implemented and a comparison of time complexity of the processing is presented at the end.