SIGformer: Sign-aware Graph Transformer for Recommendation

This is the PyTorch implementation for our SIGIR 2024 paper.

Sirui Chen, Jiawei Chen, Sheng Zhou, Bohao Wang, Shen Han, Chanfei Su, Yuqing Yuan, Can Wang 2024. SIGformer: Sign-aware Graph Transformer for Recommendation arXiv link

Environment

• python==3.9.19
• numpy==1.26.4
• pandas==2.2.1
• scipy==1.12.0
• torch==2.2.2
• pyg==2.5.2
• torchsparsegradutils==0.1.2

Datasets

Dataset	#Users	#Items	#Interactions	Pos/Neg
Amazon-CDs	51,267	46,464	895,266	1:0.22
Amazon-Music	3,472	2,498	49,875	1:0.25
Epinions	17,894	17,660	413,774	1:0.37
KuaiRec	1,411	3,327	253,983	1:5.95
KuaiRand	16,974	4,373	263,100	1:1.25

Training & Evaluation

• Amazon-CDs

  python -u code/main.py --data=amazon-cds --offset=4 --alpha=0.4 --beta=1 --sample_hop=2

• Amazon-Music

  python -u code/main.py --data=amazon-music --offset=4 --alpha=0.0 --beta=1 --sample_hop=3

• Epinions

  python -u code/main.py --data=epinions --offset=4 --alpha=0.4 --beta=1 --sample_hop=3

• KuaiRec

  python -u code/main.py --data=KuaiRec --offset=1 --alpha=-0.8 --beta=-0.2 --sample_hop=6

• KuaiRand

  python -u code/main.py --data=KuaiRand --offset=1 --alpha=0.2 --beta=1 --sample_hop=3

Citation

If you find the paper useful in your research, please consider citing:

@inproceedings{chen2024sigformer,
  title={SIGformer: Sign-aware Graph Transformer for Recommendation},
  author={Chen, Sirui and Chen, Jiawei and Zhou, Sheng and Wang, Bohao and Han, Shen and Su, Chanfei and Yuan, Yuqing and Wang, Can},
  booktitle={Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  pages={1274--1284},
  year={2024}
}