GNN-DSR

This code is for the paper "Graph Neural Networks with Dynamic and Static Representations for Social Recommendation" which is accepted by DASFAA 2022.

This paper proposes a PyTorch framework called GNN-DSR for social recommendation.

Requirements

• Python 3.8
• CUDA 11.3
• PyTorch 1.8.1
• NumPy 1.19.2
• Pandas 1.1.3
• tqdm 4.50.2

Get Started

1. Install all the requirements.

2. Train and evaluate the GNN-DSR using the Python script main.py.
   To reproduce the results on Ciao in our paper, you can run

   python main.py --test

   To see the detailed usage of main.py, you can run

   python main.py -h

3. Preprocess the datasets using the Python script preprocess.py.
   For example, to preprocess the Ciao dataset, you can run

   python preprocess.py --dataset Ciao

   The above command will store the preprocessed data files in folder datasets/Ciao.

   Raw Datasets (Ciao and Epinions) can be downloaded at http://www.cse.msu.edu/~tangjili/trust.html

   To see the detailed usage of preprocess.py, you can run

   python preprocess.py -h