CNN with depthwise separable convolutions and combined kernels for rating prediction

作者：

Highlights：

• A deep learning model using CNN with depthwise separable convolutions on review text.

• These convolutions with multiple parallel kernels better infer the hidden features.

• The features obtained in this way give better user/item repersentation;context-aware.

• Experimental results validates the claim and outperfroms the baseline alternatives.

摘要

•A deep learning model using CNN with depthwise separable convolutions on review text.•These convolutions with multiple parallel kernels better infer the hidden features.•The features obtained in this way give better user/item repersentation;context-aware.•Experimental results validates the claim and outperfroms the baseline alternatives.

论文关键词：Convolutional neural networks,Rating prediction,Deep learning,Reviews,Depthwise separable convolutions,E-learning

论文评审过程：Received 28 May 2019, Revised 12 November 2020, Accepted 19 December 2020, Available online 25 December 2020, Version of Record 15 January 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114528