Explicit Behavior Interaction with Heterogeneous Graph for Multi-behavior Recommendation

Explicit Behavior Interaction with Heterogeneous Graph for Multi-behavior Recommendation

Abstract Multi-behavior recommendation systems exploit multi-type user–item interactions (e.g., clicking, adding to cart and collecting) as auxiliary behaviors for user modeling, which can alleviate the problem of data sparsity faced by traditional recommendation systems. The key point of multi-beha...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Zhongping Zhang, Yin Jia, Yuehan Hou, Xinlu Yu
Format: Artykuł
Język:English
Wydane: SpringerOpen 2024-01-01
Seria:Data Science and Engineering
Hasła przedmiotowe:
Multi-behavior recommendation
Collaborative filtering
Heterogeneous graph
Explicit behavior interaction
Dostęp online:https://doi.org/10.1007/s41019-023-00238-3

Internet

https://doi.org/10.1007/s41019-023-00238-3

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