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Huazhong University of Science and Technology
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Fine-grained interest extraction in search and recommendation can dramatically boost accuracy, revealing user preferences that traditional models overlook.
Stop disjointedly predicting ratings and explanations in recommendation systems: Curr-RLCER uses reinforcement learning to ensure they actually make sense together.
