Source code of our MMGCL
If you want to use our codes in your research, please cite:
@inproceedings{yi2022multi,
title={Multi-modal graph contrastive learning for micro-video recommendation},
author={Yi, Zixuan and Wang, Xi and Ounis, Iadh and Macdonald, Craig},
booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages={1807--1811},
year={2022}
}
The codes of PGCL are implemented and tested under the following development environment:
- numba==0.53.1
- numpy==1.20.3
- scipy==1.6.2
- torch==1.10.3
- torch_scatter==2.0.6
- Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
- Run main.py and choose the model you want to run.
You can find the full version of recommendation datasets via Tiktok, and Movielens. Since the copyright of datasets, we cannot release them directly.
We tend to submit this version to the multi modal recommendation library shortly.