SpotTarget

Paper: Jing Zhu*, Yuhang Zhou*, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices.

Link: https://arxiv.org/abs/2306.00899

Citation (bibtex):

@inproceedings{caper,
  title={Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices.},
  author={Jing Zhu*, Yuhang Zhou*, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra},
  booktitle={WSDM},
  year={2024}
}

Training-time Usage

For use as an excluder within the DGL library, check this merged pull requests: dmlc/dgl#5893.

Example usages are as follows:

low_degree_excluder = dgl.dataloading.SpotTarget(
        g,
        exclude="reverse_id",
        degree_threshold=degree_threshold,
        reverse_eids=reverse_eids,
    )
sampler = dgl.dataloading.as_edge_prediction_sampler(
        sampler,
        exclude=low_degree_excluder,
        negative_sampler=dgl.dataloading.negative_sampler.Uniform(1),
    )

For using it separately, check RFC_low_degree_sampler.md

Test-time Usage

python3 leakage_check.py

Due to the size of the graph, The E-commerce graph used in paper are available upon request.

Question & troubleshooting

If you encounter any problems running the code, pls feel free to contact Jing Zhu (jingzhuu@umich.edu)