DAP

This is our implementation for the paper 'How Graph Convolutions Amplify Popularity Bias for Recommendation?' published at Frontiers of Computer Science

    @article{JiajiachenDAP2023,
    author = {Jiajia CHEN, Jiancan WU, Jiawei CHEN, Xin XIN, Yong LI, Xiangnan HE},
    title = {How Graph Convolutions Amplify Popularity Bias for Recommendation?},
    publisher = {Front. Comput. Sci.},
    year = {},
    journal = {Frontiers of Computer Science},
    volume = {},
    number = {},
    eid = {0},
    numpages = {0},
    pages = {0},
    keywords = {},
    url = {https://journal.hep.com.cn/fcs/EN/abstract/article_35103.shtml},
    doi = {10.1007/s11704-023-2655-2}
    }    

You can run this method by modify the model.py in [LightGCN-Pytorch/code] (https://github.com/gusye1234/LightGCN-PyTorch)