Latest development of clustering ensemble

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (11): 142-144.

• 数据库、信号与信息处理 • Previous Articles Next Articles

Latest development of clustering ensemble

YANG Yan¹,JIN Fan¹,KAMEL Mohamed²

1.School of Information Science and Technology，Southwest Jiaotong University，Chengdu 610031，China
2.Department of Electrical and Computing Engineering，University of Waterloo，Waterloo N2L 3G1，Canada

Received:2007-09-29 Revised:2007-11-12 Online:2008-04-11 Published:2008-04-11
Contact: YANG Yan

聚类组合研究的新进展

杨燕¹,靳蕃¹,KAMEL Mohamed²

1.西南交通大学信息科学与技术学院，成都 610031
2.加拿大滑铁卢大学电子与计算机工程系，安大略滑铁卢 N2L 3G1

通讯作者: 杨燕

Abstract

Abstract: As a novel research hotspot of clustering analysis currently，clustering ensemble can improve the performance of data clustering by combining two or multiple clustering algorithms.Some latest research results on clustering diversity and consensus function are reviewed，and a clustering ensemble method inspired by neural network ensemble is presented.Finally the future research issues are discussed.

Key words: clustering ensemble, diversity component, consensus function, neural network ensemble

摘要： 作为目前聚类分析的新兴研究热点，聚类组合方法能将两种或多种聚类方法集成起来以改善其性能。从聚类多样性和共识函数两方面综述了最新研究进展，探讨将神经网络组合的思想用于聚类组合。最后指出了将来可能的研究方向。

关键词: 聚类组合, 多样性分量, 共识函数, 神经网络组合

YANG Yan¹,JIN Fan¹,KAMEL Mohamed². Latest development of clustering ensemble[J]. Computer Engineering and Applications, 2008, 44(11): 142-144.

杨燕¹,靳蕃¹,KAMEL Mohamed². 聚类组合研究的新进展[J]. 计算机工程与应用, 2008, 44(11): 142-144.

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Latest development of clustering ensemble

聚类组合研究的新进展

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