A hierarchical recommendation system for E-commerce using online user reviews

作者：

Highlights：

• We propose a hierarchical recommendation system for e-commerce domain that uses online user reviews.

• Our recommendation system uses not only item title and description, but also item’s reviews when generating item embedding vectors.

• We provide an analysis of using all item reviews and randomly selected item reviews when making a recommendation.

• We provide a transparent recommendation system that capable of explaining all recommendations.

摘要

•We propose a hierarchical recommendation system for e-commerce domain that uses online user reviews.•Our recommendation system uses not only item title and description, but also item’s reviews when generating item embedding vectors.•We provide an analysis of using all item reviews and randomly selected item reviews when making a recommendation.•We provide a transparent recommendation system that capable of explaining all recommendations.

论文关键词：Deep Learning,Sequential recommendation models,Bidirectional encoder representations,Hierarchical recommendation models

论文评审过程：Received 14 August 2021, Revised 15 February 2022, Accepted 15 February 2022, Available online 23 February 2022, Version of Record 26 February 2022.

论文官网地址：https://doi.org/10.1016/j.elerap.2022.101131