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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 ...
The Unfairness of Collaborative Filtering Algorithms’ Bias Towards Blockbuster Items
(Ocak, 2023)
It is known that collaborative filtering recommendation algorithms are usually biased towards some particular items (e.g., popular) in their produced ranked lists. In this study, we evaluate this problem from the perspective ...