Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering
Author:
Affiliation:
1. Jinan University,Guangzhou,China
2. Zhejiang University,Hangzhou,China
3. The Hong Kong Polytechnic University,Hong Kong SAR,China
4. South China Agricultural University,Guangzhou,China
5. Guangdong University of Finance,Guangzhou,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10411504/10411508/10411514.pdf?arnumber=10411514
Reference30 articles.
1. A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
2. A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions
3. Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction
4. A Survey of Collaborative Filtering Techniques
5. Neural Collaborative Filtering
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Behavior Pattern Mining-based Multi-Behavior Recommendation;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10
2. CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13
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