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ENTITY Uncertainty-Calibrated Recommendations for Low-Active Users

Uncertainty-Calibrated Recommendations for Low-Active Users

PulseAugur coverage of Uncertainty-Calibrated Recommendations for Low-Active Users — every cluster mentioning Uncertainty-Calibrated Recommendations for Low-Active Users across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_38680 ·

    Recommender systems use uncertainty to boost user retention and diversity

    Researchers have developed a new framework to improve recommender systems by quantifying model uncertainty. This approach allows for differentiated strategies, such as risk-averse deboosting for low-activity users to su…