Incorporating textual reviews in the learning of latent factors for recommender systems
作者：
Highlights：
• We use textual reviews to support the ratings in the latent factor model.
• A review is interpreted as a description of the user/item and a description of the surrounding elements.
• A latent factor model is proposed to account for both interpretations.
• Reviews are incorporated not only into objective function but also into the initialization.
摘要
•We use textual reviews to support the ratings in the latent factor model.•A review is interpreted as a description of the user/item and a description of the surrounding elements.•A latent factor model is proposed to account for both interpretations.•Reviews are incorporated not only into objective function but also into the initialization.
论文关键词：Latent factor model,Collaborative filtering,Review-based recommendation,Recommender systems
论文评审过程：Received 25 September 2021, Revised 30 January 2022, Accepted 22 February 2022, Available online 2 March 2022, Version of Record 11 March 2022.
论文官网地址：https://doi.org/10.1016/j.elerap.2022.101133
