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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書誌詳細

主要な著者:	Yuzhe Chen, Qiong Cao, Xianying Huang, Shihao Zou
フォーマット:	Artigo
言語:	Inglês
出版事項:	Springer 2024-04-01
シリーズ:	Complex & Intelligent Systems
主題:	Sequential recommendation Multi-behavior recommendation Contrastive learning Graph neural network
オンライン･アクセス:	https://doi.org/10.1007/s40747-024-01423-1
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