MEMN:Multiple Vectors Embedding for Multi-Label Networks

doi:10.1109/ACCESS.2018.2878870

	MEMN:Multiple Vectors Embedding for Multi-Label Networks
	Pu, Juhua 1,2; Liu, Zhuang 1,2; Chen, Yujun 1,2; Liu, Xingwu 3,4
	2018
发表期刊	IEEE ACCESS
ISSN	2169-3536
卷号	6 页码:66143-66152
摘要	Network embedding, which assigns vectors to network nodes in a manner that preserves the network features, is a hotspot of network research in recent years. A salient common feature of the existing approaches is that each node is mapped to exactly one vector. This one-vector mapping is insufficient to represent the nodes' attribution in those extensively existed networks whose nodes' have multiple labels. In this paper, we present MEMN, a novel approach of multiple vectors embedding for multi-labeled networks. For any node in the network, MEMN employs Node2vecWalk to generate its neighbor nodes. We maintain a neighbor cluster center for each label of the node and induce its label by clustering the embeddings of the neighbor nodes. Then, we assign vectors, one per label, to the node. This method can be non-parameterized, namely, NP-MEMN method. That is, if the number of label vectors for a node is not given, NP-MEMN can learn during embedding. Empirical studies on real datasets show that either MEMN or NP-MEMN outperforms many widely used methods in both multi-label classification and link prediction.
关键词	Network embedding multiple vectors multi-label classification link prediction
DOI	10.1109/ACCESS.2018.2878870
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2017YFB1002000] ; National Natural Science Foundation of China[61502320] ; Science Foundation of Shenzhen City in China ; State Key Laboratory of Software Development Environment
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000452407300001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/3505
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Liu, Xingwu
作者单位	1.Beihang Univ, Res Inst, Shenzhen 518057, Peoples R China 2.Beihang Univ, Engn Res Ctr ACAT, Minist Educ, Beijing 100191, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Pu, Juhua,Liu, Zhuang,Chen, Yujun,et al. MEMN:Multiple Vectors Embedding for Multi-Label Networks[J]. IEEE ACCESS,2018,6:66143-66152.
APA	Pu, Juhua,Liu, Zhuang,Chen, Yujun,&Liu, Xingwu.(2018).MEMN:Multiple Vectors Embedding for Multi-Label Networks.IEEE ACCESS,6,66143-66152.
MLA	Pu, Juhua,et al."MEMN:Multiple Vectors Embedding for Multi-Label Networks".IEEE ACCESS 6(2018):66143-66152.