Title
Group event recommendation based on graph multi-head attention network combining explicit and implicit information
Abstract
•We establish a general group event recommendation framework in EBSN.•We alleviate the problem of sparse data in group recommendation and solve the problem of learning vector redundancy.•We produce better user and event vector representations by using the multi-head attention mechanism.•Experimental results on two real-world datasets demonstrate that the proposed model significantly outperforms state-of-the-art methods on group event recommendation.
Year
DOI
Venue
2022
10.1016/j.ipm.2021.102797
Information Processing & Management
Keywords
DocType
Volume
Explicit information,Implicit information,Group recommendation,Graph attention network
Journal
59
Issue
ISSN
Citations 
2
0306-4573
0
PageRank 
References 
Authors
0.34
4
4
Name
Order
Citations
PageRank
Guoqiong Liao1268.36
Xiaobin Deng200.34
Changxuan Wan300.34
Xiping Liu400.34