Efficient Clustering Aggregation Based on Data Fragments

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	Efficient Clustering Aggregation Based on Data Fragments
	Wu, Ou1 ; Hu, Weiming1 ; Maybank, Stephen J.2; Zhu, Mingliang 1; Li, Bing1 ; Ou Wu
发表期刊	IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
	2012-06-01
卷号	42 期号:3 页码:913-926
文章类型	Article
摘要	Clustering aggregation, known as clustering ensembles, has emerged as a powerful technique for combining different clustering results to obtain a single better clustering. Existing clustering aggregation algorithms are applied directly to data points, in what is referred to as the point-based approach. The algorithms are inefficient if the number of data points is large. We define an efficient approach for clustering aggregation based on data fragments. In this fragment-based approach, a data fragment is any subset of the data that is not split by any of the clustering results. To establish the theoretical bases of the proposed approach, we prove that clustering aggregation can be performed directly on data fragments under two widely used goodness measures for clustering aggregation taken from the literature. Three new clustering aggregation algorithms are described. The experimental results obtained using several public data sets show that the new algorithms have lower computational complexity than three well-known existing point-based clustering aggregation algorithms (Agglomerative, Furthest, and LocalSearch); nevertheless, the new algorithms do not sacrifice the accuracy.
关键词	Clustering Aggregation Comparison Measure Computational Complexity Data Fragment Fragment-based Approach Mutual Information Point-based Approach
WOS标题词	Science & Technology ; Technology
关键词[WOS]	ENSEMBLE ; CLASSIFIERS ; PARTITIONS ; ALGORITHM ; CONSENSUS ; NET
收录类别	SCI
语种	英语
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000304163200027
引用统计	被引频次：29[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3276
专题	多模态人工智能系统全国重点实验室_视频内容安全
通讯作者	Ou Wu
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ London, Birkbeck Coll, Sch Comp Sci & Informat Syst, London WC1E 7HX, England
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Wu, Ou,Hu, Weiming,Maybank, Stephen J.,et al. Efficient Clustering Aggregation Based on Data Fragments[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,2012,42(3):913-926.
APA	Wu, Ou,Hu, Weiming,Maybank, Stephen J.,Zhu, Mingliang,Li, Bing,&Ou Wu.(2012).Efficient Clustering Aggregation Based on Data Fragments.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,42(3),913-926.
MLA	Wu, Ou,et al."Efficient Clustering Aggregation Based on Data Fragments".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 42.3(2012):913-926.

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