A hybrid recommendation system with many-objective evolutionary algorithm

作者：

Highlights：

• Recommend the more and novel items based on accurate and diverse recommendations.

• Mixing multiple recommendation technologies to improve recommendation performance.

• The system is based on rating, which makes the recommendation more objective.

• Clustering strategies are used to reduce recommended consumption.

摘要

•Recommend the more and novel items based on accurate and diverse recommendations.•Mixing multiple recommendation technologies to improve recommendation performance.•The system is based on rating, which makes the recommendation more objective.•Clustering strategies are used to reduce recommended consumption.

论文关键词：Recommendation systems,Many-objective optimization,Hybrid recommender algorithm,Collaborative filtering

论文评审过程：Received 18 August 2019, Revised 5 June 2020, Accepted 8 June 2020, Available online 20 June 2020, Version of Record 26 June 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113648