Knowledge Commons of Institute of Automation,CAS
Multi-view clustering via joint feature selection and partially constrained cluster label learning | |
Yin, Qiyue1; Zhang, Junge1; Wu, Shu1; Li, Hexi2 | |
发表期刊 | PATTERN RECOGNITION |
ISSN | 0031-3203 |
2019-09-01 | |
卷号 | 93页码:380-391 |
通讯作者 | Zhang, Junge(jgzhang@nlpr.ia.ac.cn) ; Li, Hexi() |
摘要 | Real world data are often represented by multiple distinct feature sets, and some prior knowledge is provided, such as labels of some examples or pairwise constraints between several sample pairs. Accordingly, task of multi-view clustering arises from a complex information aggregation of multiple sources of feature sets and knowledge prior. In this paper, we propose to optimize the cluster indicator, which representing the class labels is an intuitive reflection of the clustering structure. Besides, the prior indicating the same level of semantics can be directly utilized guiding the learned clustering structure. Furthermore, feature selection is embedded into the above process to select views and features in each view, which leads to the most discriminative views and features chosen for every single cluster. To these ends, an objective is accordingly proposed with an efficient optimization strategy and convergence analysis. Extensive experiments demonstrate that our model performs better than the state-of-the-art methods. (C) 2019 Elsevier Ltd. All rights reserved. |
关键词 | Multi-view clustering Feature selection Prior information Cluster indicator |
DOI | 10.1016/j.patcog.2019.04.024 |
关键词[WOS] | SPARSE ; FRAMEWORK |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2016YFB1001004] ; National Natural Science Foundation of China[61876181] ; Guangdong Natural Science Foundation[2016A030313003] ; National Key Research and Development Program of China[2016YFB1001004] ; National Natural Science Foundation of China[61876181] ; Guangdong Natural Science Foundation[2016A030313003] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Guangdong Natural Science Foundation |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000472697800029 |
出版者 | ELSEVIER SCI LTD |
七大方向——子方向分类 | 模式识别基础 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/26146 |
专题 | 智能系统与工程 |
通讯作者 | Zhang, Junge; Li, Hexi |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 2.Wuyi Univ, Fac Intelligent Mfg, Jiangmen, Guangdong, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yin, Qiyue,Zhang, Junge,Wu, Shu,et al. Multi-view clustering via joint feature selection and partially constrained cluster label learning[J]. PATTERN RECOGNITION,2019,93:380-391. |
APA | Yin, Qiyue,Zhang, Junge,Wu, Shu,&Li, Hexi.(2019).Multi-view clustering via joint feature selection and partially constrained cluster label learning.PATTERN RECOGNITION,93,380-391. |
MLA | Yin, Qiyue,et al."Multi-view clustering via joint feature selection and partially constrained cluster label learning".PATTERN RECOGNITION 93(2019):380-391. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论