Common information guide heuristic clustering algorithm

doi:10.3778/j.issn.1002-8331.2010.31.014

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (31): 50-53.DOI: 10.3778/j.issn.1002-8331.2010.31.014

• 研究、探讨 • Previous Articles Next Articles

Common information guide heuristic clustering algorithm

JIN Ping¹，ZONG Yu^2，3，LI Ming-chu²

1.Department of Computer Science and Technology，West Anhui University，Liuan，Anhui 237012，China
2.School of Software，Dalian University or Technology，Dalian，Liaoning 116621，China
3.Centre for Applied Informatics，Victoria University，VIC 8001，Melbourne Australia

Received:2010-01-19 Revised:2010-03-19 Online:2010-11-01 Published:2010-11-01
Contact: JIN Ping

共有信息引导的启发式聚类算法

金萍¹，宗瑜^2，3，李明楚²

1.皖西学院计算机科学与技术系，安徽六安 237012
2.大连理工大学软件学院，辽宁大连 116621
3.澳大利亚维多利亚大学信息应用中心，VIC 8001

通讯作者: 金萍

Abstract

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

摘要： 启发式聚类算法采用局部搜索策略发现使得目标函数取极小值的聚类结果，即局部最优聚类结果。算法虽然具有收敛速度快等优点，但是初始解敏感问题严重地影响了聚类结果的质量。利用多个局部最优聚类结果中的共有信息设计启发式聚类算法。首先给出共有信息的定义及其发现算法FCI_G；然后利用共有信息设计启发式聚类算法CIGC；最后在多组仿真和实际数据集上考察了CIGC算法的性能。实验结果表明，共有信息对提高聚类算法质量有着显著的作用。

关键词: 聚类分析, 启发式聚类算法, 共有信息

CLC Number:

TP18

JIN Ping¹，ZONG Yu^2，3，LI Ming-chu². Common information guide heuristic clustering algorithm[J]. Computer Engineering and Applications, 2010, 46(31): 50-53.

金萍¹，宗瑜^2，3，李明楚². 共有信息引导的启发式聚类算法[J]. 计算机工程与应用, 2010, 46(31): 50-53.

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Common information guide heuristic clustering algorithm

共有信息引导的启发式聚类算法

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