Whole-Chain Recommendations

@article{Zhao2020WholeChainR,
  title={Whole-Chain Recommendations},
  author={X. Zhao and Long Xia and Lixin Zou and H. Liu and D. Yin and Jiliang Tang},
  journal={Proceedings of the 29th ACM International Conference on Information & Knowledge Management},
  year={2020}
}
  • X. Zhao, Long Xia, +3 authors Jiliang Tang
  • Published 2020
  • Computer Science
  • Proceedings of the 29th ACM International Conference on Information & Knowledge Management
    • With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in developing RL-based recommender systems. In practical recommendation sessions, users will sequentially access multiple scenarios, such as the entrance pages and the item detail pages, and each scenario has its specific characteristics. However, the majority of existing RL-based recommender systems focus on optimizing one strategy for all scenarios or separately optimizing each strategy, which… CONTINUE READING
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