Study of Text Emotion Analysis Based on Deep Learning

被引:0
作者
Xia, Fan [1 ,2 ]
Zhang, Zhi [1 ,2 ]
机构
[1] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430065, Hubei, Peoples R China
[2] Hubei Prov Key Lab Intelligent Informat Proc & Re, Wuhan 430065, Hubei, Peoples R China
来源
PROCEEDINGS OF THE 2018 13TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2018) | 2018年
关键词
deep learning; convolutional neural networks; recurrent neural networks; short and long-term memory recurrent neural networks Introduction;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In traditional sentiment classification methods, sentiment-based methods rely heavily on the quality and coverage of sentiment lexicons, whereas machine-based approaches rely on features of manual construction and decimation. In recent years, deep learning technology has made great progress in the field of natural language processing, depth model has more powerful skills. This article focuses on several commonly used deep learning models for textual affective classification and compares their strengths and weaknesses.
引用
收藏
页码:2716 / 2720
页数:5
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