福建电脑2024，Vol.40Issue(4)：20-24,5.DOI:10.16707/j.cnki.fjpc.2024.04.005
融合多头注意力和ConvBiLSTM的文本情感分析
Text Sentiment Analysis Integrating Multi-head Attention and ConvBiLSTM
摘要
Abstract
In order to better predict and understand the development trend of public emotions and public opinion,this paper uses CNN and BiLSTM to capture local and global features of text,strengthens the model's attention to key information through multi head attention mechanism,explores the impact of emoticons on text classification,and constructs an efficient sentiment analysis model ECBL-MHA for online public opinion processing.The experimental results show that the ECBL-MHA model achieves an accuracy of 90.51%in text classification prediction,which is feasible for application in sentiment analysis.关键词
卷积神经网络/长短期记忆网络/多头注意力机制/表情符号/情感分析Key words
CNN/BiLSTM/Multi-Head Attention/Emoji/Sentiment Analysis分类
信息技术与安全科学引用本文复制引用
王彬彬,李晓晔..融合多头注意力和ConvBiLSTM的文本情感分析[J].福建电脑,2024,40(4):20-24,5.基金项目
本文得到黑龙江省省属高等学校基本科研业务费科研项目(No.145209124)资助. （No.145209124）
