Aspect Sentiment Classification Towards Question-Answering with Reinforced Bidirectional Attention Network
Jingjing Wang, Changlong Sun, Shoushan Li, Xiaozhong Liu, Luo Si, Min Zhang, Guodong Zhou · 2019
In the literature, existing studies on aspect sentiment classification (ASC) focus on individual non-interactive reviews.This paper extends the research to interactive reviews and proposes a new research task, namely Aspect Sentiment Classification towards Question-Answering (ASC-QA), for real-world applications.This new task aims to predict sentiment polarities for specific aspects from interactive QA style reviews.In particular, a high-quality annotated corpus is constructed for ASC-QA to facilitate corresponding research.On this basis, a Reinforced Bidirectional Attention Network (RBAN) approach is proposed to address two inherent challenges in ASC-QA, i.e., semantic matching between question and answer, and data noise.Experimental results demonstrate the great advantage of the proposed approach to ASC-QA against several state-of-the-art baselines.