ONTOLOGY BASED CLUSTERING IN RESEARCH PROJECT SELECTION & ASSIGN PROPOSALS TO EXPERTS BY ONTOLOGY MATCHING

Abstract

Research Project Selection is a remarkable bustle in all Research funding and Government agencies. Selection and Assignment processes are unproblematic when number of proposal submission is less. But with mounting in numbers, both processes will become complicated. Through traditional methodologies, Proposal Grouping, Experts grouping and Proposal assignment to experts are done manually or via keywords which yield inefficient results. In recent methodologies, Ontology based Text Mining Method (OTMM) has been used to cluster Proposals based on their likeness in research area by means of Research Ontology. Whereas, Reviewers grouping and proposal assignment to experts is still not precise since it is done manually. This paper proposes Ontology based Text Mining Method to cluster reviewers based on their specialism and overcome the Ontology Mapping Problem to allocate proposals to appropriate reviewers analytically. This methodology affords an effective way for research project selection with escalating figure of proposals and reviewers.