Sequential Recommendation with Graph Neural Networks

@article{Chang2021SequentialRW,
  title={Sequential Recommendation with Graph Neural Networks},
  author={Jianxin Chang and Chen Gao and Y. Zheng and Yiqun Hui and Yanan Niu and Yang Song and Depeng Jin and Yong Li},
  journal={Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year={2021}
}
  • Jianxin Chang, Chen Gao, Yong Li
  • Published 27 June 2021
  • Computer Science
  • Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
Sequential recommendation aims to leverage users' historical behaviors to predict their next interaction. Existing works have not yet addressed two main challenges in sequential recommendation. First, user behaviors in their rich historical sequences are often implicit and noisy preference signals, they cannot sufficiently reflect users' actual preferences. In addition, users' dynamic preferences often change rapidly over time, and hence it is difficult to capture user patterns in their… 

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