User trends modeling for a content-based recommender system

作者：

Highlights：

• Proposing a novel evolutionary model-based recommender system.

• Introducing the concept of trend to capture dynamics in user interests.

• Proposing a Bayesian nonparametric model to construct the trend distributions.

• Adapting the trend-based user model in line with temporal activities of user.

摘要

•Proposing a novel evolutionary model-based recommender system.•Introducing the concept of trend to capture dynamics in user interests.•Proposing a Bayesian nonparametric model to construct the trend distributions.•Adapting the trend-based user model in line with temporal activities of user.

论文关键词：User trends,Content-based recommender systems,User modeling

论文评审过程：Received 21 November 2016, Revised 8 May 2017, Accepted 13 June 2017, Available online 13 June 2017, Version of Record 21 June 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.06.020