面向问答文本的属性级情感分类研究 (Attribute Sentiment Classification Towards Question-answering Text)
Jiang, M., Lee, S. Y. M., Liu, H., & Li, S. (2019). 面向问答文本的属性级情感分类研究. 计算机科学 (Computer Science), 46(11A).
Abstract
The goal of conditional sentiment analysis is getting the sentiment polarity of whole text,which is a coarsetask.Recently,with the improved technology,the sentiment analysis task is also refined,and the researchers hope to get sentiment polarity of given target of the text.This paper’s purpose is getting the sentiment polarity of product attribute on question-answering text.To perform attribute sentiment classification towards QA text pair,this paper proposed a novel approach based on attention mechanism.Firstly,this paper concatenated the attribute information on answer words’ vectors.Secondly,this paper leveraged LSTM models to encode the question text and answer text.Thirdly,this paper got the relation of question and answer by using attention mechanism and got the whole feature of answer.Finally,this paper got the result of whole feature by using classifier.Empirical studies demonstrate the effectiveness of the proposed approach to attribute sentiment classification towards question-answering text.
