Contrastive Curriculum Learning for Sequential User Behavior Modeling via Data Augmentation

Author:

Bian Shuqing1,Zhao Wayne Xin1,Zhou Kun1,Cai Jing2,He Yancheng2,Yin Cunxiang2,Wen Ji-Rong1

Affiliation:

1. Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China

2. Tencent, Shenzhen, China

Publisher

ACM

Reference53 articles.

Cited by 22 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. Enhanced Self-supervised Graph Learning Algorithm for Social Recommendation;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. TriMLP : A Foundational MLP-like Architecture for Sequential Recommendation;ACM Transactions on Information Systems;2024-06-10

3. Meta-Optimized Joint Generative and Contrastive Learning for Sequential Recommendation;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

4. Rethinking Sequential Relationships: Improving Sequential Recommenders with Inter-Sequence Data Augmentation;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

5. Multi-source information contrastive learning collaborative augmented conversational recommender systems;Complex & Intelligent Systems;2024-05-11

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