Using Text Mining and Clustering to Group Research Proposals for Research Project Selection

Yibo Wang, Wei Xu, Hongxun Jiang

Abstract: Great efforts have been taken to guarantee the efficiency of research project selection. Before research proposals are assigned to appropriate experts for evaluation, research proposals needed to be grouped according to their similarities in research topics. This paper applies an ensemble method to cluster research proposals to support research project selection. Several cluster algorithms are applied to group the proposals and the merits of each algorithm in text clustering are made full use of in the form of ensemble method. Based on the real data from Beijing Natural Science Foundation (BNSF), empirical experiments are conducted to validate the effectiveness of the proposed method. Meanwhile, the proposed method promotes the efficiency in the proposal grouping process.