Item orientated recommendation by multi-view intact space learning with overlapping

作者：

Highlights：

• This paper proposes a new item orientated recommendation algorithm.

• It captures the latent feature vector of each item in the intact space.

• It captures the differences and overlapping preferences among different users.

• Extensive experiments have been conducted to show the effectiveness.

摘要

•This paper proposes a new item orientated recommendation algorithm.•It captures the latent feature vector of each item in the intact space.•It captures the differences and overlapping preferences among different users.•Extensive experiments have been conducted to show the effectiveness.

论文关键词：Recommendation,Item orientated,Multi-view,Intact space,Overlapping

论文评审过程：Received 5 March 2018, Revised 2 November 2018, Accepted 4 November 2018, Available online 7 November 2018, Version of Record 19 December 2018.

论文官网地址：https://doi.org/10.1016/j.knosys.2018.11.005