Cross-Network Skip-Gram Embedding for Joint Network Alignment and Link Prediction

doi:10.1109/TKDE.2020.2997861

CSpace

	Cross-Network Skip-Gram Embedding for Joint Network Alignment and Link Prediction
	Du, Xingbo 1; Yan, Junchi 2; Zhang, Rui 3; Zha, Hongyuan 4
	2022-03-01
发表期刊	IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
ISSN	1041-4347
卷号	34 期号:3 页码:1080-1095
摘要	Link prediction and network alignment are two fundamental and interleaved tasks in network analysis. In this paper, we propose a novel cross-network embedding model under the Skip-gram framework, which alternately performs link prediction and network alignment by joint optimization. Vertex sequences, obtained via a biased random walk based on empirical mixture distributions, are used to train a Skip-gram based node embedding model. On one hand, based on the similarity in embedding space, network alignment can be effectively performed either with the initial ground truth alignments as seeds or from scratch. On the other hand, the proposed link prediction model involves training a supervised classifier by sampling a set of positive and negative edges. We also modify and incorporate the Collective Link Fusion (CLF) method under a Skip-gram framework and show that the new method can achieve better results in both tasks. Extensive experimental results show the state-of-the-art performance of our methods.
关键词	Task analysis Predictive models Social network services Peer-to-peer computing Optimization Computational modeling Computer science Link prediction network alignment cross-network embedding skip-gram biased random walk
DOI	10.1109/TKDE.2020.2997861
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018AAA0100704] ; NSFC[U1609220] ; NSFC[61672231] ; NSFC[61972250] ; NSFC[U19B2035]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS记录号	WOS:000752013800006
出版者	IEEE COMPUTER SOC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/59954
专题	中国科学院数学与系统科学研究院
通讯作者	Yan, Junchi
作者单位	1.East China Normal Univ, Sch Comp Sci & Software Engn, Shanghai 200062, Peoples R China 2.Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, MoE Key Lab Artificial Intelligence, AI Inst, Shanghai 200240, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100864, Peoples R China 4.Georgia Inst Technol, Coll Comp, Atlanta, GA 30332 USA
推荐引用方式 GB/T 7714	Du, Xingbo,Yan, Junchi,Zhang, Rui,et al. Cross-Network Skip-Gram Embedding for Joint Network Alignment and Link Prediction[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2022,34(3):1080-1095.
APA	Du, Xingbo,Yan, Junchi,Zhang, Rui,&Zha, Hongyuan.(2022).Cross-Network Skip-Gram Embedding for Joint Network Alignment and Link Prediction.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,34(3),1080-1095.
MLA	Du, Xingbo,et al."Cross-Network Skip-Gram Embedding for Joint Network Alignment and Link Prediction".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 34.3(2022):1080-1095.