Selection bias mitigation in recommender system using uninteresting items based on temporal visibility
作者：
Highlights：
• Modeling pre-use preferences and temporal rating can identify uninteresting items.
• The explicit feedback of alleviating the selection bias is effective than implicit only.
• Filling with uninteresting item with discrimination can alleviates selection bias.
• The influence of selection bias on recommendation accuracy is demonstrated.
摘要
•Modeling pre-use preferences and temporal rating can identify uninteresting items.•The explicit feedback of alleviating the selection bias is effective than implicit only.•Filling with uninteresting item with discrimination can alleviates selection bias.•The influence of selection bias on recommendation accuracy is demonstrated.
论文关键词：Collaborative filtering,Explicit feedback,Selection bias,Pre-use preference,Uninteresting items
论文评审过程：Received 19 November 2021, Revised 18 September 2022, Accepted 25 September 2022, Available online 30 September 2022, Version of Record 3 October 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118932
