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	High-order possibilistic c-means algorithms based on tensor decompositions for big data in IoT
	Zhang, Qingchen; Yang, Laurence T.; Chen, Zhikui; Li, Peng
刊名	INFORMATION FUSION
	2018
卷号	39页码:72-80
关键词	Big data IoT Possibilistic c-means clustering Canonical polyadic decomposition Tensor-train network
ISSN号	1566-2535
URL标识	查看原文
WOS记录号	[DB:DC_IDENTIFIER_WOSID]
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/3277045
专题	大连理工大学
作者单位	1.Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu, Sichuan, Peoples R China.,St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS, Canada. 2.Dalian Univ Technol, Sch Software Technol, Dalian, Peoples R China.
推荐引用方式 GB/T 7714	Zhang, Qingchen,Yang, Laurence T.,Chen, Zhikui,et al. High-order possibilistic c-means algorithms based on tensor decompositions for big data in IoT[J]. INFORMATION FUSION,2018,39:72-80.
APA	Zhang, Qingchen,Yang, Laurence T.,Chen, Zhikui,&Li, Peng.(2018).High-order possibilistic c-means algorithms based on tensor decompositions for big data in IoT.INFORMATION FUSION,39,72-80.
MLA	Zhang, Qingchen,et al."High-order possibilistic c-means algorithms based on tensor decompositions for big data in IoT".INFORMATION FUSION 39(2018):72-80.

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