ILWAANet: An Interactive Lexicon-Aware Word-Aspect Attention Network for aspect-level sentiment classification on social networking

作者：

Highlights：

• The effcient multiple attention mechanisms can extract salient features.

• Lexicon resources as in-domain knowledge are incorporated into the neural network.

• Both Phase-level and Context-level of an aspect are captured effectively.

摘要

•The effcient multiple attention mechanisms can extract salient features.•Lexicon resources as in-domain knowledge are incorporated into the neural network.•Both Phase-level and Context-level of an aspect are captured effectively.

论文关键词：Social media,Deep learning,Aspect-level sentiment analysis

论文评审过程：Received 11 October 2018, Revised 23 October 2019, Accepted 26 October 2019, Available online 28 November 2019, Version of Record 16 January 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113065