An Ontology based Text Mining framework for R&D Project Selection

Abstract

Research and development (R&D) project selection is an decision-making task commonly found in government funding agencies, universities, research institutes, and technology intensive companies. Text Mining has emerged as a definitive technique for extracting the unknown information from large text document. Ontology is a knowledge repository in which concepts and terms are defined as well as relationships between these concepts. Ontology's make the task of searching similar pattern of text that to be more effective, efficient and interactive. The current method for grouping proposals for research project selection is proposed using an ontology based text mining approach to cluster research proposals based on their similarities in research area. This method is efficient and effective for clustering research proposals. However proposal assignment regarding research areas to experts cannot be often accurate. This paper presents a framework on ontology based text mining to cluster research proposals, external reviewers based on their research area and to assign concerned research proposals to reviewers systematically. A knowledge based agent is appended to the proposed system for a retrieval of data from the system in an efficient way.