A weighted multi-attribute-based recommender system using extended user behavior analysis

作者：

Highlights：

• A weighted multi-attribute based recommender system is proposed.

• It acquires and analyzes implicit and explicit feedback from users.

• The proposed RS has been applied to a movie web site and tested by 567 users.

• The results of the proposed RS for detailed analysis are better than results of CF.

摘要

•A weighted multi-attribute based recommender system is proposed.•It acquires and analyzes implicit and explicit feedback from users.•The proposed RS has been applied to a movie web site and tested by 567 users.•The results of the proposed RS for detailed analysis are better than results of CF.

论文关键词：Collaborative filtering,Evolutionary algorithms,Recommender systems,Relevance feedback,User behavior analysis

论文评审过程：Received 23 July 2017, Revised 24 January 2018, Accepted 24 January 2018, Available online 31 January 2018, Version of Record 26 March 2018.

论文官网地址：https://doi.org/10.1016/j.elerap.2018.01.013