Heterogeneous Graph Neural Network via Attribute Completion

This repository contains the demo code of the paper:

Heterogeneous Graph Neural Network via Attribute Completion

which has been accepted by WWW2021.

Dependencies

• Python3
• NumPy
• SciPy
• scikit-learn
• NetworkX
• DGL
• PyTorch

Datasets

The preprocessed datasets are available at Baidu Netdisk(password: hgnn) or Google Drive.

Please extract the zip file to folder data.

Example

• python run_DBLP.py
• python run_IMDB.py
• python run_ACM.py

Please refer to the code for detailed parameters.

Acknowledgements

The demo code is implemented based on MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding.

Citing

@inproceedings{hgnn-ac,
 title={Heterogeneous Graph Neural Network via Attribute Completion},
 author={Di Jin and Cuiying Huo and Chundong Liang and Liang Yang},
 booktitle = {WWW},
 year={2021}
}