SPR: Similarity pairwise ranking for personalized recommendation
作者：
Highlights：
• A pairwise method based on item similarity is proposed.
• Item similarity is used to overcome the impact of data imbalance on the pairwise ranking method.
• The method narrows the prediction score between similar item pairs in Bayesian personalized ranking method.
• A uniform sample method based on ratings is used to obtain similar item pairs.
• The method is validated in six datasets with promising results.
摘要
•A pairwise method based on item similarity is proposed.•Item similarity is used to overcome the impact of data imbalance on the pairwise ranking method.•The method narrows the prediction score between similar item pairs in Bayesian personalized ranking method.•A uniform sample method based on ratings is used to obtain similar item pairs.•The method is validated in six datasets with promising results.
论文关键词：Recommender system,Pairwise method,Similar item pair,Matrix factorization
论文评审过程：Received 12 February 2021, Revised 22 November 2021, Accepted 25 November 2021, Available online 11 December 2021, Version of Record 1 January 2022.
论文官网地址：https://doi.org/10.1016/j.knosys.2021.107828
