• Computer Science, Mathematics
  • Published in ArXiv 2019

Recommendation System-based Upper Confidence Bound for Online Advertising

@article{NguyenThanh2019RecommendationSU,
  title={Recommendation System-based Upper Confidence Bound for Online Advertising},
  author={Nhan Nguyen-Thanh and Dana Marinca and Kinda Khawam and David Rohde and Flavian Vasile and Elena Simona Lohan and Steven Martin and Dominique Quadri},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.04190}
}
In this paper, the method UCB-RS, which resorts to recommendation system (RS) for enhancing the upper-confidence bound algorithm UCB, is presented. The proposed method is used for dealing with non-stationary and large-state spaces multi-armed bandit problems. The proposed method has been targeted to the problem of the product recommendation in the online advertising. Through extensive testing with RecoGym, an OpenAI Gym-based reinforcement learning environment for the product recommendation in… CONTINUE READING

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