Pair-wise Preference Relation based Probabilistic Matrix Factorization for Collaborative Filtering in Recommender System
作者：
Highlights：
• A novel preference relation based collaborative filtering model is proposed.
• The proposed model can capture both second and higher order user-item interactions.
• Side information is integrated using matrix co-factorization framework.
• The proposed model is evaluated using standard ranking measures like NDCG and MAP.
• The proposed model is compared with the current state-of-the-art related methods.
摘要
•A novel preference relation based collaborative filtering model is proposed.•The proposed model can capture both second and higher order user-item interactions.•Side information is integrated using matrix co-factorization framework.•The proposed model is evaluated using standard ranking measures like NDCG and MAP.•The proposed model is compared with the current state-of-the-art related methods.
论文关键词：Recommender System,Probabilistic Matrix Factorization,Collaborative Filtering,Side Information
论文评审过程：Received 18 February 2019, Revised 17 March 2020, Accepted 19 March 2020, Available online 24 March 2020, Version of Record 16 April 2020.
论文官网地址：https://doi.org/10.1016/j.knosys.2020.105798
