关键词: 聚类分析, 启发式聚类算法, 共有信息

Abstract: Heuristic clustering algorithm generates the local suboptimal clustering results which make the objective function converge to local minimum with local search method.Although，the convergences speed of heuristic clustering algorithm is fast，but the initialization sensitivity problem make it cannot guarantee the quality of clustering results.In this paper，the common information derived from several local suboptimal clustering results is used to design heuristic clustering algorithm.The common information definition and its finding algorithm，FCI_G is given；the common information is used to design algorithm CIGC；the efficient of CIGC is tested on several synthetic and real world data sets.Experiment results show that common information has significant efforts on improving the clustering results.

Key words: clustering analysis, heuristic clustering algorithm, common Information