Contextual-boosted deep neural collaborative filtering model for interpretable recommendation

作者：

Highlights：

• Recommendation performance is improved by leveraging textual introductions of items.

• An interactive attention network is used to combine the rating and introduction information.

• Experimental results show the effectiveness of our model for rating prediction.

摘要

•Recommendation performance is improved by leveraging textual introductions of items.•An interactive attention network is used to combine the rating and introduction information.•Experimental results show the effectiveness of our model for rating prediction.

论文关键词：Recommendation systems,Interpretable recommendation,Interactive attention network,Collaborative filtering,Cold start problem

论文评审过程：Received 6 September 2018, Revised 24 June 2019, Accepted 24 June 2019, Available online 26 June 2019, Version of Record 1 July 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.06.051