Basket-Enhanced Heterogenous Hypergraph for Price-Sensitive Next Basket Recommendation
<|reference_start|>Basket-Enhanced Heterogenous Hypergraph for Price-Sensitive Next Basket Recommendation: Next Basket Recommendation (NBR) is a new type of recommender system that predicts combinations of items users are likely to purchase together. Existing NBR models often overlook a crucial factor, which is price, and do not fully capture item-basket-user interactions. To address these limitations, we propose a novel method called Basket-augmented Dynamic Heterogeneous Hypergraph (BDHH). BDHH utilizes a heterogeneous multi-relational graph to capture the intricate relationships among item features, with price as a critical factor. Moreover, our approach includes a basket-guided dynamic augmentation network that could dynamically enhances item-basket-user interactions. Experiments on real-world datasets demonstrate that BDHH significantly improves recommendation accuracy, providing a more comprehensive understanding of user behavior.<|reference_end|>
@article{zhou2024basket-enhanced,
    title={Basket-Enhanced Heterogenous Hypergraph for Price-Sensitive Next Basket
  Recommendation},
    author={Yuening Zhou, Yulin Wang, Qian Cui, Xinyu Guan, Francisco Cisternas},
    journal={arXiv preprint arXiv:2409.11695},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.11695},
    primaryClass={cs.IR}
}