An adaptive fuzzy recommender system based on learning automata
作者：
Highlights：
• We propose a learning automata-based method for optimizing membership functions.
• The proposed method adjusts the number and the position of membership functions.
• The proposed method can be used without any change in any fuzzy recommender system.
• The performance of proposed method is tested on well-known datasets.
• The results show that the proposed method improves the recommendation accuracy.
摘要
•We propose a learning automata-based method for optimizing membership functions.•The proposed method adjusts the number and the position of membership functions.•The proposed method can be used without any change in any fuzzy recommender system.•The performance of proposed method is tested on well-known datasets.•The results show that the proposed method improves the recommendation accuracy.
论文关键词：Social networks,Recommender systems,Trust,Distrust,Fuzzy linguistic modelling,Learning automata
论文评审过程：Received 5 June 2016, Revised 27 August 2016, Accepted 4 October 2016, Available online 13 October 2016, Version of Record 26 October 2016.
论文官网地址：https://doi.org/10.1016/j.elerap.2016.10.002
