软件导刊2024，Vol.23Issue(1)：190-196,7.DOI:10.11907/rjdk.231075
基于局部全局上下文引导的方面级情感分析
Aspect Sentiment Analysis Based on Local-Global Context Guidance
摘要
Abstract
Sentiment analysis is one of the important directions in the field of natural language processing.Existing researches on the influ-ence of context of exploration still has insufficient challenges such as difficulty in syntax information capture,loss of semantic information,and lack of semantic context.Aiming at these problems,propose a novel combination of local global context guidance network to improve the performance and expression ability in the aspect-based sentiment analysis.Specifically,in this method,a dependency syntax parsing tree is constructed firstly to introduce more diversified information features for the model;Then,by introducing the context focusing mechanism,the characteristics of the original text and dependency syntax parsing tree are refined.At the same time,the local feature vector of the refining is interacted with the global feature vector so as to retain the context feature information of the words effectively.Finally,the characteristic aggre-gation module is aggregated to the local global characteristics,which improves the accuracy of the model in emotional polarity prediction.The experimental results on the four benchmark datasets show that compared with the baseline models,the accuracy of the proposed model increas-es by 1.67%,1.67%,0.7%and 0.16%respectively,and the F1 value increases by 2.55%,2.03%,1.57%and 2.08%respectively.关键词
情感分析/自然语言处理/局部上下文/依赖句法分析树/信息特征Key words
sentiment analysis/natural language processing/local context/dependency syntax parsing tree/information features分类
计算机与自动化引用本文复制引用
丁美荣,赖锦钱,曾碧卿,徐马一,陈炳志..基于局部全局上下文引导的方面级情感分析[J].软件导刊,2024,23(1):190-196,7.基金项目
广东省基础与应用基础研究基金项目(2021A1515011171) （2021A1515011171）
