Contrastive learning for representation degeneration problem in sequential recommendation

R Qiu, Z Huang, H Yin, Z Wang - … conference on web search and data …, 2022 - dl.acm.org
Recent advancements of sequential deep learning models such as Transformer and BERT
have significantly facilitated the sequential recommendation. However, according to our …

Self-supervised hypergraph convolutional networks for session-based recommendation

X **a, H Yin, J Yu, Q Wang, L Cui… - Proceedings of the AAAI …, 2021 - ojs.aaai.org
Session-based recommendation (SBR) focuses on next-item prediction at a certain time
point. As user profiles are generally not available in this scenario, capturing the user intent …

Self-supervised multi-channel hypergraph convolutional network for social recommendation

J Yu, H Yin, J Li, Q Wang, NQV Hung… - Proceedings of the web …, 2021 - dl.acm.org
Social relations are often used to improve recommendation quality when user-item
interaction data is sparse in recommender systems. Most existing social recommendation …

XSimGCL: Towards extremely simple graph contrastive learning for recommendation

J Yu, X **a, T Chen, L Cui… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Contrastive learning (CL) has recently been demonstrated critical in improving
recommendation performance. The underlying principle of CL-based recommendation …

Self-supervised graph co-training for session-based recommendation

X **a, H Yin, J Yu, Y Shao, L Cui - Proceedings of the 30th ACM …, 2021 - dl.acm.org
Session-based recommendation targets next-item prediction by exploiting user behaviors
within a short time period. Compared with other recommendation paradigms, session-based …