Self-supervised representation learning with ID-Content modality alignment for sequential recommendation

Donglin ZHOU; Weike PAN; Zhong MING

doi:10.1007/s11704-025-50269-4

Front. Comput. Sci. ›› 2026, Vol. 20 ›› Issue (12) : 2012624 DOI: 10.1007/s11704-025-50269-4

Information Systems

LETTER

Self-supervised representation learning with ID-Content modality alignment for sequential recommendation

Author information +

History +

PDF (865KB)

Graphical abstract

Cite this article

Download citation ▾

Donglin ZHOU, Weike PAN, Zhong MING. Self-supervised representation learning with ID-Content modality alignment for sequential recommendation. Front. Comput. Sci., 2026, 20(12): 2012624 DOI:10.1007/s11704-025-50269-4

登录浏览全文

4963

注册一个新账户忘记密码

References

Publishing order | Descend order by publishing year | Descend order by cited within

[1]	Hidasi B, Karatzoglou A, Baltrunas L, Tikk D. Session-based recommendations with recurrent neural networks. In: Proceedings of the 4th International Conference on Learning Representations. 2016

[2]	Kang W C, McAuley J. Self-attentive sequential recommendation. In: Proceedings of the IEEE International Conference on Data Mining. 2018, 197−206

[3]	Hou Y, Mu S, Zhao W X, Li Y, Ding B, Wen J R. Towards universal sequence representation learning for recommender systems. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2022, 585−593

[4]	Hou Y, He Z, McAuley J, Zhao W X. Learning vector-quantized item representation for transferable sequential recommenders. In: Proceedings of the ACM Web Conference 2023. 2023, 1162−1171

[5]	Wang J, Zeng Z, Wang Y, Wang Y, Lu X, Li T, Yuan J, Zhang R, Zheng H T, Xia S T. MISSRec: pre-training and transferring multi-modal interest-aware sequence representation for recommendation. In: Proceedings of the 31st ACM International Conference on Multimedia. 2023, 6548−6557