Evaluating content novelty in recommender systems
Journal of Intelligent Information Systems, pp. 297-316, 2019.
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
Full Text (Upload PDF)
PPT (Upload PPT)