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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Podrobná bibliografie

Hlavní autoři:	Yuzhe Chen, Qiong Cao, Xianying Huang, Shihao Zou
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Springer 2024-04-01
Edice:	Complex & Intelligent Systems
Témata:	Sequential recommendation Multi-behavior recommendation Contrastive learning Graph neural network
On-line přístup:	https://doi.org/10.1007/s40747-024-01423-1
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