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Multiview clustering via nonnegative matrix factorization based on graph agreement

文献类型：期刊论文

作者Zhang, Chengfeng3; Fu, Wenjun3; Wang, Guanglong1; Shi, Lei1; Meng, Xiangzhu2
刊名JOURNAL OF ELECTRONIC IMAGING
出版日期2022-07-01
卷号31期号:4页码:18
关键词multiview clustering nonnegative matrix factorization graph mechanism
ISSN号1017-9909
DOI10.1117/1.JEI.31.4.043024
通讯作者Meng, Xiangzhu(xiangzhu.meng@cripac.ia.ac.cn)
英文摘要With the rapid development of information technology, one object can usually be described by multiple views. Intuitively, the diversity and complementarity of different views provide a more comprehensive data description, which can lead to better performance on multiview clustering tasks. Motivated by the fact that how to fully discover diversity and complementary information across views is the key point to deal with multiview clustering, we propose a multiview learning method, termed as graph-agreement nonnegative matrix factorization (GANMF). GANMF attempts to implement this goal based on matrix factorization technology while exploiting the rich multiview information based on the intra- and interview aspects. Specifically, the graph agreement between representation space and raw space is maximized to preserve the intrinsic geometric property in individual view for the intraview case. Similarly, the graph structures in different views are expected to keep consistent with each other by minimizing the divergence between pairwise views. To this end, the intrinsic information and geometric structure information in the intraview case and complementary and compatibility information in the interview case can be simultaneously formulated into one framework. To solve the proposed GANMF, we correspondingly develop an effective algorithm based on iterative alternating strategy. Extensive experimental results on seven multiview datasets demonstrate the superiority and effectiveness of our proposed method.
资助项目National Natural Science Foundation of PRChina[61672130] ; National Natural Science Foundation of PRChina[72001191]
WOS研究方向Engineering ; Optics ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000848751400042
出版者SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
资助机构National Natural Science Foundation of PRChina
源URL[http://ir.ia.ac.cn/handle/173211/50029]  
专题自动化研究所_智能感知与计算研究中心
通讯作者Meng, Xiangzhu
作者单位1.Yanchang Petr Barasu Coal Ind Co Ltd, Yulin, Peoples R China
2.Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, Inst Automat, Beijing, Peoples R China
3.Beijing China Coal Mine Engn Co Ltd, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Chengfeng,Fu, Wenjun,Wang, Guanglong,et al. Multiview clustering via nonnegative matrix factorization based on graph agreement[J]. JOURNAL OF ELECTRONIC IMAGING,2022,31(4):18.
APA Zhang, Chengfeng,Fu, Wenjun,Wang, Guanglong,Shi, Lei,&Meng, Xiangzhu.(2022).Multiview clustering via nonnegative matrix factorization based on graph agreement.JOURNAL OF ELECTRONIC IMAGING,31(4),18.
MLA Zhang, Chengfeng,et al."Multiview clustering via nonnegative matrix factorization based on graph agreement".JOURNAL OF ELECTRONIC IMAGING 31.4(2022):18.

入库方式： OAI收割

来源：自动化研究所

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