GNN based Recommender Systems

An index of recommendation algorithms that are based on Graph Neural Networks.

Our survey Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions is available on arxiv: link

Please cite our survey paper if this index is helpful.

@article{gao2021graph,
  title={Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions},
  author={Gao, Chen and Zheng, Yu and Li, Nian and Li, Yinfeng and Qin, Yingrong and Piao, Jinghua and Quan, Yuhan and Chang, Jianxin and Jin, Depeng and He, Xiangnan and others},
  journal={arXiv preprint arXiv:2109.12843},
  year={2021}
}

Gao, C., Zheng, Y., Li, N., Li, Y., Qin, Y., Piao, J., Quan, Y., Chang, J., Jin, D., He, X., & Li, Y. (2021). Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions. arXiv preprint arXiv:2109.12843.

Table of Contents

• GNN in different recommendation stages
  • Matching
  • Ranking
  • Re-ranking
• GNN in different recommendation scenarios
  • Social Recommendation
  • Sequential Recommendation
  • Session Recommendation
  • Bundle Recommendation
  • Cross Domain Recommendation
  • Multi-behavior Recommendation
• GNN for different recommendation objectives
  • Diversity
  • Explainability
  • Fairness

Recommendation Stages

Matching

Ranking

Re-ranking

Recommendation Scenarios

Social Recommendation

Sequential Recommendation

Session Recommendation

Bundle Recommendation

Cross Domain Recommendation

Multi-behavior Recommendation

Recommendation Objectives

Diversity

Explainability

Fairness