Explore User Neighborhood for Real-time E-commerce Recommendation

@article{Xie2021ExploreUN,
  title={Explore User Neighborhood for Real-time E-commerce Recommendation},
  author={Xu Xie and Fei Sun and Xiaoyong Yang and Zhao Yang and Jinyang Gao and Wenwu Ou and Bin Cui},
  journal={2021 IEEE 37th International Conference on Data Engineering (ICDE)},
  year={2021},
  pages={2464-2475}
}
  • Xu XieFei Sun Bin Cui
  • Published 28 February 2021
  • Computer Science
  • 2021 IEEE 37th International Conference on Data Engineering (ICDE)
Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI) relations, have been widely applied in industrial settings, owing to their efficiency and effectiveness. Despite their success, we argue that these approaches ignore local information hidden in similar users. To tackle this problem, user-based methods exploit similar user relations to make recommendations in a local perspective. Nevertheless… 

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