This code is used for running experiments for the paper.
- Download the dataset file from https://mega.nz/file/wuoVTRJT#LejeGzAkdRTQu3AKOM-hYuAHwM0eg1pVDBT2AQ4nxF8 and unzip
- Install all dependencies in the requirements.txt
- Run the following command to get all results:
export PYTHONPATH=.;python train_EdgeAttributed.py --data_folder "$(pwd)/data" | tee run.log - 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