/MGCN

Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction. KDD2020

Primary LanguagePython

This is the source code of the paper: Hongxu Chen, Hongzhi Yin, Xiangguo Sun, Tong Chen, Bogdan Gabrys and Katarzyna Musial. Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction. 26th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'20), San Diego, USA. August, 2020

To run the source code:

  • Step1: use 1.preprocess.py to get graph partition, and other necessary variables.
  • Step2: use 2.model.py to learn node embeddings of each partition.
  • Step3: use 3.1 and 3.2 to match embeddings between partitions and networks
  • Step4: use 4.anchor_predict.py to predict anchor links

Prerequisite

pytorch
python-louvain
networkx

Please cite our paper if you use this code

citation:

@inproceedings{chen2020multi,
  title={Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction},
  author={Chen, Hongxu and Yin, Hongzhi and Sun, Xiangguo and Chen, Tong and Gabrys, Bogdan and Musial, Katarzyna},
  booktitle={26th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'20)},
  year={2020}
}