A rough set-based association rule approach for a recommendation system for online consumers
作者：
Highlights：
• It is increased the importance of understanding online consumers’ purchase behaviors.
• Recommendation systems are decision aids that analyze customer's prior online behavior.
• This study proposes a rough set-based association rule approach.
• It is developed from ordinal data scale processing for customer’s preference analysis.
• We find some patterns and rules for e-commerce platform recommendations.
摘要
•It is increased the importance of understanding online consumers’ purchase behaviors.•Recommendation systems are decision aids that analyze customer's prior online behavior.•This study proposes a rough set-based association rule approach.•It is developed from ordinal data scale processing for customer’s preference analysis.•We find some patterns and rules for e-commerce platform recommendations.
论文关键词：Data mining,Rough set,Association rule,Rough set association rule,Analytic hierarchy process,Recommendation systems
论文评审过程：Received 27 November 2015, Revised 3 May 2016, Accepted 7 May 2016, Available online 24 May 2016, Version of Record 28 September 2016.
论文官网地址：https://doi.org/10.1016/j.ipm.2016.05.003
