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[AAAI'25] STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation

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STAIR

PyTorch implementation of "STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation". (arXiv)

framework

Environment Setup

Requirements: Python >= 3.9 | PyTorch >=2.0 | TorchData >=0.6.0 | PyG >=2.3

conda create -n stair python=3.9;conda activate stair;bash env.sh

Datasets

All datasets used in this project can be accessed via Google Drive.

Usage

cd STAIR
python main.py --config configs/Amazon2014Baby_550_MMRec.yaml

Citation

If you find STAIR useful in your research, please kindly cite:

@article{xu2024stair,
    title={STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation},
    author={Xu, Cong and He, Yunhang and Wang, Jun and Zhang, Wei},
    journal={arXiv preprint arXiv:2412.11729},
    year={2024}
}

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