This is a Tensorflow implementation of the Fuzzy-based Deep Attributed Graph Clustering (FDAGC)
Our experiments are mainly conducted on citation datasets and social datasets.
For these two types of datasets, Cora dataset and Facebook dataset are taken as examples to demonstrate in the code.
- TensorFlow 2.0
- python 3.6
- numpy
- network 2.3
- scipy 1.5
- scikit-learn 0.22
For Cora dataset:
python train_cora.py
For Facebook dataset:
python train_facebook.py
All results can be viewed in the result directory.
Due to upload limitations, all datasets are given in: Url：https://pan.baidu.com/s/1dcsatrHDzAhcUN9kwOfB_w?pwd=xiv3
If you use code or datasets in this repository for your research, please cite our paper.
@ARTICLE{10339895, author={Yang, Yue and Su, Xiaorui and Zhao, Bowei and Li, GuoDong and Hu, Pengwei and Zhang, Jun and Hu, Lun}, journal={IEEE Transactions on Fuzzy Systems}, title={Fuzzy-Based Deep Attributed Graph Clustering}, year={2024}, volume={32}, number={4}, pages={1951-1964}, keywords={Clustering algorithms;Task analysis;Representation learning;Training;Optimization;Convolution;Computational modeling;Attributed graph (AG) clustering;fuzzy clustering;graph convolution;graph representation learning;node embeddings}, doi={10.1109/TFUZZ.2023.3338565}}