Modeling user preferences using neural networks and tensor factorization model
作者：
Highlights：
• Determined relevant contextual dimensions by multilayer perceptron neural network.
• Articulated contextual dimensions prominently using tensor factorization model.
• Improvement in accuracy due to utilization of relevant contextual dimensions.
• Prediction performance of Neural Networks and Tensor Factorization is comparable.
摘要
•Determined relevant contextual dimensions by multilayer perceptron neural network.•Articulated contextual dimensions prominently using tensor factorization model.•Improvement in accuracy due to utilization of relevant contextual dimensions.•Prediction performance of Neural Networks and Tensor Factorization is comparable.
论文关键词：Context-aware recommendations,Contextual modeling,Consumer satisfaction level,Dimensionality reduction,Neural networks,Tensor factorization
论文评审过程：Received 15 May 2018, Revised 13 October 2018, Accepted 13 October 2018, Available online 21 November 2018, Version of Record 21 November 2018.
论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2018.10.010
