中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Deep auto-encoder based clustering

文献类型:期刊论文

作者Song, Chunfeng1; Huang, Yongzhen2; Liu, Feng3; Wang, Zhenyu1; Wang, Liang2
刊名INTELLIGENT DATA ANALYSIS
出版日期2014
卷号18页码:S65-S76
关键词Clustering deep auto-encoder non-linear transformation complicated data
英文摘要For unsupervised problems like clustering, linear or non-linear data transformations are widely used techniques. Generally, they are beneficial to data representation. However, if data have a complicated structure, these techniques would be unsatisfying for clustering. In this paper, we propose a new clustering method based on the deep auto-encoder network, which can learn a highly non-linear mapping function. Via simultaneously considering data reconstruction and compactness, our method can obtain stable and effective clustering. Experimental results on four databases demonstrate that the proposed model can achieve promising performance in terms of normalized mutual information, cluster purity and accuracy.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
关键词[WOS]NEURAL-NETWORKS ; RECOGNITION
收录类别SCI
语种英语
WOS记录号WOS:000347782000006
源URL[http://ir.ia.ac.cn/handle/173211/3804]  
专题自动化研究所_智能感知与计算研究中心
作者单位1.North China Elect Power Univ, Sch Control & Comp, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
3.Southeast Univ, Sch Automat, Nanjing, Jiangsu, Peoples R China
推荐引用方式
GB/T 7714
Song, Chunfeng,Huang, Yongzhen,Liu, Feng,et al. Deep auto-encoder based clustering[J]. INTELLIGENT DATA ANALYSIS,2014,18:S65-S76.
APA Song, Chunfeng,Huang, Yongzhen,Liu, Feng,Wang, Zhenyu,&Wang, Liang.(2014).Deep auto-encoder based clustering.INTELLIGENT DATA ANALYSIS,18,S65-S76.
MLA Song, Chunfeng,et al."Deep auto-encoder based clustering".INTELLIGENT DATA ANALYSIS 18(2014):S65-S76.

入库方式: OAI收割

来源:自动化研究所

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