An official source code for paper CONVERT:Contrastive Graph Clustering with Reliable Augmentation, accepted by ACM MM 23. Any communications or issues are welcomed. Please contact xihong_edu@163.com. If you find this repository useful to your research or work, it is really appreciate to star this repository. ❤️
Illustration of CONVERT:Contrastive Graph Clustering with Reliable Augmentation mechanism.
The proposed CONVERT is implemented with python 3.8.8 on a NVIDIA 2080 Ti GPU.
Python package information is summarized in requirements.txt:
- torch==1.8.0
- tqdm==4.61.2
- numpy==1.21.0
- tensorboard==2.8.0
python train.py
If you use code or datasets in this repository for your research, please cite our paper.
@inproceedings{CONVERT,
title={CONVERT: Contrastive Graph Clustering with Reliable Augmentation},
author={Yang, Xihong and Tan, Cheng and Liu, Yue and Liang, Ke and Wang, Siwei and Zhou, Sihang and Xia, Jun and Li, Stan Z and Liu, Xinwang and Zhu, En},
booktitle={Proceedings of the 31th ACM International Conference on Multimedia},
pages={},
year={2023}
}