S-NGCF

Socially-aware neural graph collaborative filtering
This project is based on https://github.com/xiangwang1223/neural_graph_collaborative_filtering
We increase social connection to user-item bipartite graph to analyze social influence on recommendation.

If you want to use our codes and datasets in your research, please cite both:

@inproceedings{NGCF19,
  author    = {Xiang Wang and
               Xiangnan He and
               Meng Wang and
               Fuli Feng and
               Tat{-}Seng Chua},
  title     = {Neural Graph Collaborative Filtering},
  booktitle = {Proceedings of the 42nd International {ACM} {SIGIR} Conference on
               Research and Development in Information Retrieval, {SIGIR} 2019, Paris,
               France, July 21-25, 2019.},
  pages     = {165--174},
  year      = {2019},
}

@inproceedings{tsai2019predicting,
  title={Predicting New Adopters via Socially-Aware Neural Graph Collaborative Filtering},
  author={Tsai, Yu-Che and Guan, Muzhi and Li, Cheng-Te and Cha, Meeyoung and Li, Yong and Wang, Yue},
  booktitle={International Conference on Computational Data and Social Networks},
  pages={155--162},
  year={2019},
  organization={Springer}
}

For details, please run:
python NGCF.py -h
in the NGCF folder