GHRS: Graph-based hybrid recommendation system with application to movie recommendation

作者：

Highlights：

• We propose a recommendation system using graph-based features and Autoencoders.

• We investigate and analyze each step of the method to find the best setup.

• We examine the method with the most popular evaluation metrics and datasets.

• Results show an improvement in comparison with basic and state of the art methods.

摘要

•We propose a recommendation system using graph-based features and Autoencoders.•We investigate and analyze each step of the method to find the best setup.•We examine the method with the most popular evaluation metrics and datasets.•Results show an improvement in comparison with basic and state of the art methods.

论文关键词：Recommendation system,Deep learning,Graph-based modeling,Autoencoder,Cold-start

论文评审过程：Received 22 November 2020, Revised 4 March 2022, Accepted 6 March 2022, Available online 18 March 2022, Version of Record 7 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116850