NFGCL: A Negative-sampling-free Graph Contrastive Learning Framework for Recommendation
Our model is in "recbole_gnn/model/general_recommender/nfgcl.py"
If you want to run the model, you can add our code files to the Recbole-GNN-main (an open-source library: https://github.com/RUCAIBox/RecBole-GNN.git) and then edit the file run_recbole_gnn.py.
For example (dataset=Gowalla):
import argparse
from recbole_gnn.quick_start import run_recbole_gnn
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model', '-m', type=str, default='NFGCL', help='name of models')
parser.add_argument('--dataset', '-d', type=str, default='Gowalla', help='name of datasets')
parser.add_argument('--config_files', type=str, default='recbole_gnn/properties/overall.yaml recbole_gnn/properties/dataset/gowalla.yaml', help='config files')
args, _ = parser.parse_known_args()
config_file_list = args.config_files.strip().split(' ') if args.config_files else None
run_recbole_gnn(model=args.model, dataset=args.dataset, config_file_list=config_file_list)
Thank you for your attention! :)