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MGCN: Multi-View Graph Convolutional Network for Multimedia Recommendation

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Introduction

This is the Pytorch implementation for our MM 2023 paper:

MM 2023. Penghang Yu, Zhiyi Tan, Guanming Lu, Bing-Kun Bao(2023). Multi-View Graph Convolutional Network for Multimedia Recommendation

<img src="image/framework.png" width="900px" height="306px"/>

Enviroment Requirement

Dataset

We provide three processed datasets: Baby, Sports and Clothing.

Download from Google Drive: Baby/Sports/Clothing

Training

cd ./src
python main.py

Performance Comparison

<img src="image/result.png" width="900px" height="380px"/>

Citing MGCN

If you find MGCN useful in your research, please consider citing our paper.

@article{yu2023multi,
  title={Multi-View Graph Convolutional Network for Multimedia Recommendation},
  author={Yu, Penghang and Tan, Zhiyi and Lu, Guanming and Bao, Bing-Kun},
  booktitle={Proceedings of the 31st ACM International Conference on Multimedia},
  pages = {6576–6585},
  year={2023}
}

The code is released for academic research use only. For commercial use, please contact Penghang Yu.

Acknowledgement

The structure of this code is based on MMRec. Thank for their work.