Diversity analysis of information pattern and information clustering algorithm

  • Authors:

  • Shifei Ding;Wei Ning;Zhongzhi Shi

  • Affiliations:

  • School of Computer Science and Technology, China University of Mining and Technoogy, Xuzhou, P.R. China and Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, ...;School of Computer Science and Technology, Xuzhou Normal University, Xuzhou, P.R. China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing P.R. China

  • Venue:
  • ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
  • Year:
  • 2007

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Abstract

According to information theory, a basic concept of the measure of diversity is defined, and a basic inequation of the measure of diversity is discussed and proved, then a concept of increment of diversity is given. The diversity of the information pattern is carried out the analysis. On the basis of theses discussions, the information coefficient measure (ICM) is defined, and a new information clustering algorithm is built up according to the ICM, and then carried out the information clustering analysis for soil fertility data processing in land. Compared with Hierarchical Clustering Algorithm (HCA) traditionally, the result of simulated application shows that the algorithm presented here is feasible and effective.