FRAIPA version 2: A fast recommendation approach based on self-adaptation and multi-thresholding

作者：

Highlights：

• A fast recommendation approach is proposed.

• The approach is based on self-adaptation and multi-thresholding.

• An automatic convergence procedure is proposed to improve the performance of our approach.

• The MAE is improved between 1.02% and 12.93%, and the computational time between 25.38% and 54.83%.

摘要

•A fast recommendation approach is proposed.•The approach is based on self-adaptation and multi-thresholding.•An automatic convergence procedure is proposed to improve the performance of our approach.•The MAE is improved between 1.02% and 12.93%, and the computational time between 25.38% and 54.83%.

论文关键词：Collaborative filtering,Sparsity,Rating prediction,Recommender system

论文评审过程：Received 20 July 2017, Revised 29 September 2018, Accepted 30 September 2018, Available online 1 October 2018, Version of Record 13 October 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.09.055