A recommendation algorithm based on fine-grained feature analysis
作者：
Highlights：
• Users’ historical reviews with knowledge graphs explore the fine-grained features.
• The framework could learn representations of users and items for recommending.
• Our framework embed user behavior into underlying representation via fine-tuning.
• Extensive results demonstrate the superiority of our proposed method.
摘要
•Users’ historical reviews with knowledge graphs explore the fine-grained features.•The framework could learn representations of users and items for recommending.•Our framework embed user behavior into underlying representation via fine-tuning.•Extensive results demonstrate the superiority of our proposed method.
论文关键词：Knowledge graph,Recommender system,Fine-grained features,Collaborative learning
论文评审过程：Received 10 April 2019, Revised 26 February 2020, Accepted 12 July 2020, Available online 18 July 2020, Version of Record 1 September 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113759
