Research and Development (R&D) project proposals selection is one of the decision-making task commonly found in government funding agencies, universities, research institutes, and technology intensive companies. With the rapid development of research work in projects, research project selection & classification into different domain is a necessary task for the research funding agencies. It is common to group the large number of research proposals, received by the research funding agencies based on their similarities into research discipline areas. Text Mining has emerged as a definitive technique for extracting the unknown information from large text document for the proposal classification. Ontology is a knowledge repository in which concepts and terms are defined as well as relationships between these concepts. Thus, ontology can automate information processing and can facilitate text mining in a specific domain (such as research project selection). This paper presents approach towards ontology-based text-mining to cluster research proposals based on their similarities in research areas. The method also includes an optimization model for balancing proposals by geographical regions. The grouped proposals are then assign to the appropriate research experts for peer-review through system itself. The proposed method is milestone over the manual approach for classifying proposals.