Matrix completion incorporating auxiliary information for recommender system design

作者：

Highlights：

• Generalized matrix completion framework incorporating user’s demographic.

• Efficient algorithm based on split Bregman technique to solve proposed formulation.

• Extensive experiments to study impact of various factors on prediction accuracy.

摘要

•Generalized matrix completion framework incorporating user’s demographic.•Efficient algorithm based on split Bregman technique to solve proposed formulation.•Extensive experiments to study impact of various factors on prediction accuracy.

论文关键词：Collaborative filtering,Matrix completion,Metadata,Latent factor model

论文评审过程：Available online 10 April 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.04.012