The use of machine learning algorithms in recommender systems: A systematic review
作者：
Highlights：
• A survey of machine learning (ML) algorithms in recommender systems (RSs) is provided.
• The surveyed studies are classified in different RS categories.
• The studies are classified based on the types of ML algorithms and application domains.
• The studies are also analyzed according to main and alternative performance metrics.
• LNCS and EWSA are the main sources of studies in this research field.
摘要
•A survey of machine learning (ML) algorithms in recommender systems (RSs) is provided.•The surveyed studies are classified in different RS categories.•The studies are classified based on the types of ML algorithms and application domains.•The studies are also analyzed according to main and alternative performance metrics.•LNCS and EWSA are the main sources of studies in this research field.
论文关键词：Systematic review of the literature,Recommender systems,Machine learning,Machine learning algorithms,Application domains,Performance metrics
论文评审过程：Received 27 May 2016, Revised 7 December 2017, Accepted 8 December 2017, Available online 9 December 2017, Version of Record 23 December 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.020
