Approximate pairwise clustering for large data sets via sampling plus extension
文献类型：期刊论文
| 作者 | Wang, Liang1 ; Leckie, Christopher2; Kotagiri, Ramamohanarao2; Bezdek, James2
|
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2011-02-01 |
| 卷号 | 44期号:2页码:222-235 |
| 关键词 | Pairwise data Selective sampling Spectral clustering Graph embedding Out-of-sample extension |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | ALGORITHMS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000284446200005 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/9735]  |
| 专题 | 自动化研究所_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 |
| 推荐引用方式 GB/T 7714 | 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. |
入库方式： OAI收割
来源：自动化研究所
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