Exploiting multimodal interactions in recommender systems with ensemble algorithms
作者：
Highlights：
• The developed recommender tool contains three ensemble approaches.
• Developed approaches were based on different types of users׳ feedback.
• Our techniques are extensible and flexible for different types of users׳ feedback.
• The ensemble mechanism provides better results in recommender systems.
• The ensemble learning technique offers better results when compared to others.
摘要
Highlights•The developed recommender tool contains three ensemble approaches.•Developed approaches were based on different types of users׳ feedback.•Our techniques are extensible and flexible for different types of users׳ feedback.•The ensemble mechanism provides better results in recommender systems.•The ensemble learning technique offers better results when compared to others.
论文关键词：User profiles,Recommender systems,User interactions,Ensemble approaches
论文评审过程：Received 10 September 2015, Accepted 19 September 2015, Available online 30 September 2015, Version of Record 22 October 2015.
论文官网地址：https://doi.org/10.1016/j.is.2015.09.007
