MGCN: Multi-View Graph Convolutional Network for Multimedia Recommendation

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

Enviroment Requirement

python 3.8
Pytorch 1.12

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

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.

demonph10/MGCN