A Novel Attention-based Global and Local Information Fusion Neural Network for Group Recommendation

doi:10.1007/s11633-022-1336-1

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	A Novel Attention-based Global and Local Information Fusion Neural Network for Group Recommendation
	Song Zhang1,2 ; Nan Zheng1,2 ; Dan-Li Wang 1,2
发表期刊	Machine Intelligence Research
ISSN	2731-538X
	2022
卷号	19 期号:4 页码:331-346
摘要	Due to the popularity of group activities in social media, group recommendation becomes increasingly significant. It aims to pursue a list of preferred items for a target group. Most deep learning-based methods on group recommendation have focused on learning group representations from single interaction between groups and users. However, these methods may suffer from data sparsity problem. Except for the interaction between groups and users, there also exist other interactions that may enrich group representation, such as the interaction between groups and items. Such interactions, which take place in the range of a group, form a local view of a certain group. In addition to local information, groups with common interests may also show similar tastes on items. Therefore, group representation can be conducted according to the similarity among groups, which forms a global view of a certain group. In this paper, we propose a novel global and local information fusion neural network (GLIF) model for group recommendation. In GLIF, an attentive neural network (ANN) activates rich interactions among groups, users and items with respect to forming a group′s local representation. Moreover, our model also leverages ANN to obtain a group′s global representation based on the similarity among different groups. Then, it fuses global and local representations based on attention mechanism to form a group′s comprehensive representation. Finally, group recommendation is conducted under neural collaborative filtering (NCF) framework. Extensive experiments on three public datasets demonstrate its superiority over the state-of-the-art methods for group recommendation.
关键词	Group recommendation attentive neural network (ANN) global information local information recommender system
DOI	10.1007/s11633-022-1336-1
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55949
专题	学术期刊_Machine Intelligence Research
作者单位	1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Song Zhang,Nan Zheng,Dan-Li Wang. A Novel Attention-based Global and Local Information Fusion Neural Network for Group Recommendation[J]. Machine Intelligence Research,2022,19(4):331-346.
APA	Song Zhang,Nan Zheng,&Dan-Li Wang.(2022).A Novel Attention-based Global and Local Information Fusion Neural Network for Group Recommendation.Machine Intelligence Research,19(4),331-346.
MLA	Song Zhang,et al."A Novel Attention-based Global and Local Information Fusion Neural Network for Group Recommendation".Machine Intelligence Research 19.4(2022):331-346.

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