Evaluating content novelty in recommender systems
Journal of Intelligent Information Systems, pp. 297-316, 2019.
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Recommender systems are frequently evaluated using performance indexes based on variants and extensions of precision-like measures. As these measures are biased toward popular items, a list of recommendations simply must include a few popular items to perform well. To address the popularity bias challenge, new approaches for novelty and d...More
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