The official code of ICDM2022 paper: [Structure-Preserving Graph Representation Learning]
Ruiyi Fang, Liangjian Wen, Zhao Kang, Jianzhuang Liu
We propose a new Structure-Preserving Graph Representation Learning method called SPGRL. Our main idea is maximizing the mutual information (MI) between the graph structure and feature embedding.
The module is illustrated as follows:
- python == 3.8
- Pytorch == 1.1.0
- Numpy == 1.16.2
- SciPy == 1.3.1
- Networkx == 2.4
- scikit-learn == 0.21.3
python main.py -d dataset -l labelrate
- dataset: including [citeseer, uai, acm, BlogCatalog, flickr, cora], required.
- labelrate: including [20, 40, 60], required.
e.g.
python main.py -d citeseer -l 20