SCAGC

This repo provides a demo for the TMM-2022 article: Self-consistent Contrastive Attributed Graph Clustering with Pseudo-label Prompt on the ACM dataset.

Requirements

• Python 3.6
• PyTorch 1.6.0
• PyTorch Geometric 1.6.1

Training

-Step 1: Warm-Up:

python \ACM-Pretrain-1\Pre_train_1.py

Once the training is finished, then remember copy the generated Pre_train_1.pkl to the folder ACM-Pretrain-2:

python \ACM-Pretrain-2\Pretrain_2.py

Once the training is finished, then remember copy the generated ACM_pretrain.pkl to the folder ACM-Final:

-Step 2: Clustering:

python \ACM-Final\run_cluster.py

Acknowledgements

Some codes are adapted from GCA and SupContrast. We thank them for their excellent projects.

Contact

If you have any problem about our code, feel free to contact xd.weixia@gmail.com or describe your problem in Issues.