CONVERT:Contrastive Graph Clustering with Reliable Augmentation

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. ❤️

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Overview

Illustration of CONVERT:Contrastive Graph Clustering with Reliable Augmentation mechanism.

Requirements

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

Quick Start

python train.py 

Citation

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}
}