Multi-behavior Hypergraph Contrastive Learning for Session-based Recommendation

Most current session-based recommendations model session sequences solely based on the user's target behavior, ignoring the user's hidden preferences in auxiliary behaviors. Additionally, they use ordinary graphs to model one-to-one item correlations in the current session and fail to leve...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2024-12, p.1-14
Hauptverfasser:	Guo, Liangmin, Zhou, Shiming, Tang, Haiyue, Zheng, Xiaoyao, Luo, Yonglong
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Contrastive learning Correlation Data mining Data models Feature extraction Hands History Hypergraph Line graph Multi-behavior Noise Session-based recommendation Vectors
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