duanchao / GDE

SIGIR 2022 Paper: Less is More: Reweighting Important Spectral Graph Features for Recommendation

GDE

Codes for the SIGIR 2022 paper Less is More: Reweighting Important Spectral Graph Features for Recommendation

Environment

The algorithm is implemented in Python 3.8.5, with the following libraries additionally needed to be installed:

• Pytorch+GPU==1.8.0
  
• Numpy==1.19.2
  
• Pandas==1.1.4
  

Due to the inefficiency of CPU, we only provide a GPU implementation. Feel free to modify the codes to adapt to your own environment.

Get Started

Two steps to run the algorithm:

1. Run preprocess.py to generate the required spectral features for the dataset. You can change the number of smoothed spectral features by adjusting 'smooth_ratio'; similarly, by adjusting 'rough_ratio', you change the number of rough spectral features.
2. Run GDE.py to generate the accuracy on test sets. Explanation on hyperparameters is provided in the codes.