A novel temporal recommender system based on multiple transitions in user preference drift and topic review evolution

作者：

Highlights：

• A novel temporal multitransition in user preference drift systems was proposed.

• It employs a multitransition factor and a forgetting time function.

• It also considers addressing the rating sparsity issue by using text reviews.

摘要

•A novel temporal multitransition in user preference drift systems was proposed.•It employs a multitransition factor and a forgetting time function.•It also considers addressing the rating sparsity issue by using text reviews.

论文关键词：Recommender system,Temporal dynamics,Collaborative filtering,Data sparsity,Topic model,User preference drift,Review-based recommender system

论文评审过程：Received 15 May 2021, Revised 28 June 2021, Accepted 14 July 2021, Available online 25 July 2021, Version of Record 28 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115626