This is the PyTorch implementation for AdaptiveGCL proposed in the paper Adaptive Graph Contrastive Learning for Recommendation.
We develop our codes in the following environment:
- python==3.9.13
- numpy==1.23.1
- torch==1.11.0
- scipy==1.9.1
Dataset | # User | # Item | # Interaction | Interaction Density |
---|---|---|---|---|
Last.FM | 1,892 | 17,632 | 92,834 | 2.8 × |
Yelp | 42,712 | 26,822 | 182,357 | 1.6 × |
BeerAdvocate | 10,456 | 13,845 | 1,381,094 | 9.5 × |
- Last.FM
python Main.py --data lastfm --eps 1e-3 --gamma -0.95
- Yelp
python Main.py --data yelp --eps 1e-3 --ssl_reg 1 --ib_reg 1e-2
- BeerAdvocate
python Main.py --data beer --ib_reg 1 --eps 1e-3 --lambda0 1e-2