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Approximate pairwise clustering for large data sets via sampling plus extension
Wang, Liang1; Leckie, Christopher2; Kotagiri, Ramamohanarao2; Bezdek, James2
2011-02-01
发表期刊PATTERN RECOGNITION
卷号44期号:2页码:222-235
文章类型Article
摘要Pairwise clustering methods have shown great promise for many real-world applications. However, the computational demands of these methods make them impractical for use with large data sets. The contribution of this paper is a simple but efficient method, called eSPEC, that makes clustering feasible for problems involving large data sets. Our solution adopts a "sampling, clustering plus extension" strategy. The methodology starts by selecting a small number of representative samples from the relational pairwise data using a selective sampling scheme; then the chosen samples are grouped using a pairwise clustering algorithm combined with local scaling; and finally, the label assignments of the remaining instances in the data are extended as a classification problem in a low-dimensional space, which is explicitly learned from the labeled samples using a cluster-preserving graph embedding technique. Extensive experimental results on several synthetic and real-world data sets demonstrate both the feasibility of approximately clustering large data sets and acceleration of clustering in loadable data sets of our method. (C) 2010 Elsevier Ltd. All rights reserved.
关键词Pairwise Data Selective Sampling Spectral Clustering Graph Embedding Out-of-sample Extension
WOS标题词Science & Technology ; Technology
关键词[WOS]ALGORITHMS
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000284446200005
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9735
专题智能感知与计算研究中心
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Melbourne, Dept Comp Sci & Software Engn, Parkville, Vic 3010, Australia
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Wang, Liang,Leckie, Christopher,Kotagiri, Ramamohanarao,et al. Approximate pairwise clustering for large data sets via sampling plus extension[J]. PATTERN RECOGNITION,2011,44(2):222-235.
APA Wang, Liang,Leckie, Christopher,Kotagiri, Ramamohanarao,&Bezdek, James.(2011).Approximate pairwise clustering for large data sets via sampling plus extension.PATTERN RECOGNITION,44(2),222-235.
MLA Wang, Liang,et al."Approximate pairwise clustering for large data sets via sampling plus extension".PATTERN RECOGNITION 44.2(2011):222-235.
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