User preferences prediction approach based on embedded deep summaries

作者：

Highlights：

• A hybrid approach to learn and represent users’ preference knowledge.

• Users’ preference knowledge representation supplements ratings prediction.

• Extending latent factor model to include acquired preference knowledge.

• Experiments on Amazon products datasets shows performance improvements.

摘要

•A hybrid approach to learn and represent users’ preference knowledge.•Users’ preference knowledge representation supplements ratings prediction.•Extending latent factor model to include acquired preference knowledge.•Experiments on Amazon products datasets shows performance improvements.

论文关键词：User preference prediction,Text summarization,Deep learning embedding

论文评审过程：Received 30 November 2018, Revised 19 April 2019, Accepted 19 April 2019, Available online 25 April 2019, Version of Record 8 May 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.047