NeuLP: An End-to-End Deep-Learning Model for Link Prediction

Reference : NeuLP: An End-to-End Deep-Learning Model for Link Prediction


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/44544

Title :	NeuLP: An End-to-End Deep-Learning Model for Link Prediction
Language :	English
Author, co-author :	Zhong, Zhiqiang [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
	Zhang, Yang []
	Pang, Jun [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) > ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)]
Publication date :	2020
Main document title :	Proceedings of the 21st International Conference on Web Information System Engineering (WISE'20)
Publisher :	Springer
Collection and collection volume :	LNCS 12342
Pages :	96-108
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	21st International Conference on Web Information System Engineering
Event date :	2020
Target :	Researchers ; Students
Permalink :	http://hdl.handle.net/10993/44544
FnR project :	FnR ; FNR10621687 > Sjouke Mauw > SPsquared > Security and Privacy for System Protection > 01/01/2017 > 30/06/2023 > 2016

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Open access	WISE20a.pdf		Author preprint	912.57 kB	View/Open

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