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Learning from Atypical Behavior: Temporary Interest Aware Recommendation Based on Reinforcement Learning
2022 · arXiv (Cornell University)
Traditional robust recommendation methods view atypical user-item interactions as noise and aim to reduce their impact with some kind of noise filtering technique, which often suffers from two challenges. First, in real world, atypical interactions …