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This code is used for running experiments for the paper.

1. Download the dataset file from https://mega.nz/file/wuoVTRJT#LejeGzAkdRTQu3AKOM-hYuAHwM0eg1pVDBT2AQ4nxF8 and unzip
2. Install all dependencies in the requirements.txt
3. Run the following command to get all results: export PYTHONPATH=.;python train_EdgeAttributed.py --data_folder "$(pwd)/data" | tee run.log
4. Check the results in run.log

Note that it will take some time to generate the cache files when you run for the first time.

Reference:

Hewen Wang, Renchi Yang, Keke Huang, and Xiaokui Xiao. 2023. Efficient and Effective Edge-wise Graph Representation Learning. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23). Association for Computing Machinery, New York, NY, USA, 2326–2336. https://doi.org/10.1145/3580305.3599321