Data mining approach in scientific research organizations evaluation via clustering

  • Authors:

  • Jingli Liu;Jianping Li;Weixuan Xu;Yong Shi

  • Affiliations:

  • University of Science & Technology of China, Hefei, P.R.C;Institute of Policy and Management, Chinese Academy of Sciences, Beijing, P.R.C;Institute of Policy and Management, Chinese Academy of Sciences, Beijing, P.R.C;Graduate School of Chinese Academy of Sciences, Beijing, P.R.C

  • Venue:
  • CASDMKM'04 Proceedings of the 2004 Chinese academy of sciences conference on Data Mining and Knowledge Management
  • Year:
  • 2004

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Abstract

Data mining is a useful tool to draw useful information from large database. In scientific research organizations evaluation, there exists a problem of using the same criteria to evaluate different types of research organizations. In this paper we propose a clustering method to make classification of the scientific research organization of CAS, and then according to this classification we evaluate the scientific research organization using the annual evaluation database of CAS to test our method.