Self-Supervised Reinforcement Learning for Recommender Systems

10 Jun 2020Xin XinAlexandros KaratzoglouIoannis ArapakisJoemon M. Jose

In session-based or sequential recommendation, it is important to consider a number of factors like long-term user engagement, multiple types of user-item interactions such as clicks, purchases etc. The current state-of-the-art supervised approaches fail to model them appropriately... (read more)

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