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Treating adverse effects of blockbuster bias on beyond-accuracy quality of personalized recommendations
(Elsevier, 2022)
Collaborative filtering recommendation algorithms are vulnerable against the popularity bias, including the most popular items repeatedly into the produced ranked lists. However, the research on popularity bias focuses ...
Exploring potential biases towards blockbuster items in ranking-based recommendations
(Springer, 2022)
Popularity bias is defined as the intrinsic tendency of recommendation algorithms to feature popular items more than unpopular ones in the ranked lists lists they produced. When investigating the adverse effects of popularity ...