Multi-behavior collaborative contrastive learning for sequential recommendation

Abstract Sequential recommendation (SR) predicts the user’s future preferences based on the sequence of interactions. Recently, some methods for SR have utilized contrastive learning to incorporate self-supervised signals into SR to alleviate the data sparsity problem. Despite these achievements, th...

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Bibliographic Details

Published in:	Complex & Intelligent Systems
Main Authors:	Yuzhe Chen, Qiong Cao, Xianying Huang, Shihao Zou
Format:	Article
Language:	English
Published:	Springer 2024-04-01
Subjects:	Sequential recommendation Multi-behavior recommendation Contrastive learning Graph neural network
Online Access:	https://doi.org/10.1007/s40747-024-01423-1