Weighted aspect-based opinion mining using deep learning for recommender system

作者：

Highlights：

• Deep learning-based aspect extraction model for building recommender system.

• Exploiting wordembedding and POS tag embedding for aspect extraction.

• Using LDA and lexicon-based method to generate aspect-based ratings.

• Integration of the aspect ratings into tensor factorization technique for rating prediction.

摘要

•Deep learning-based aspect extraction model for building recommender system.•Exploiting wordembedding and POS tag embedding for aspect extraction.•Using LDA and lexicon-based method to generate aspect-based ratings.•Integration of the aspect ratings into tensor factorization technique for rating prediction.

论文关键词：Aspect-based opinion mining,Convolutional neural network,Deep learning,Collaborative filtering,Recommender system,Rating prediction

论文评审过程：Received 2 March 2019, Revised 6 July 2019, Accepted 13 August 2019, Available online 14 August 2019, Version of Record 27 August 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.112871