BOOK-CHAPTER
A Multi-behavior Recommendation Based on Disentangled Graph Convolutional Networks and Contrastive Learning
Jie YuFeng JiangJunwei DuXu Yu
Year: 2024 Communications in computer and information science Pages: 195-207 Publisher: Springer Science+Business Media
Keywords:
Leverage (statistics) Computer science Recommender system Graph Artificial intelligence Machine learning Theoretical computer science
Metrics
0
Cited By
0.00
FWCI (Field Weighted Citation Impact)
18
Refs
0.01
Citation Normalized Percentile
Is in top 1%
Is in top 10%
Topics
Recommender Systems and Techniques
Physical Sciences → Computer Science → Information Systems
Advanced Graph Neural Networks
Physical Sciences → Computer Science → Artificial Intelligence
Caching and Content Delivery
Physical Sciences → Computer Science → Computer Networks and Communications
Related Documents
JOURNAL ARTICLE
Multi-behavior-based graph contrastive learning recommendation
Chenzhong BinWeiliang LiFangjian WuLiang ChangYimin Wen
Journal: Knowledge and Information Systems Year: 2024 Vol: 66 (6)Pages: 3477-3496
JOURNAL ARTICLE
Multi-behavior contrastive learning with graph neural networks for recommendation
Zihan ZhaoXiangrong TongYingjie WangQiang Zhang
Journal: Knowledge-Based Systems Year: 2024 Vol: 300 Pages: 112221-112221
BOOK-CHAPTER
Cascading Graph Convolution Contrastive Learning Networks for Multi-behavior Recommendation
Nan LiuShunmei MengYu JiangQianmu LiXiaolong XuLianyong QiXuyun Zhang
Lecture notes in computer science Year: 2024 Pages: 3-18
BOOK-CHAPTER
Graph Contrastive Learning for Multi-behavior Recommendation
Haiying LiHuihui WangShunmei MengXingguo Chen
Lecture notes in computer science Year: 2024 Pages: 34-48
JOURNAL ARTICLE
Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation
Zhiyong ChengJianhua DongFan LiuLei ZhuXun YangMeng Wang
Journal: ACM Transactions on Recommender Systems Year: 2024 Vol: 2 (4)Pages: 1-27