APPLICATION OF CONVOLUTIONAL NEURAL NETWORK (CNN) IN MICROBLOG TEXT CLASSIFICATION

被引：0
|
作者：
Wang, Xiaoming [1 ]
Li, Jianping [1 ]
Liu, Yifei [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 611731, Sichuan, Peoples R China
来源：
2018 15TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP) | 2018年
基金：
国家高技术研究发展计划(863计划); 中国国家自然科学基金;
关键词：
Weibo; Public opinion; Convolutional neural network; Classification;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
At present, Weibo has become the main platform of lyric fermentation in China. On this platform, Chinese people can discuss many major events, so it is very necessary to monitor the grievances on Weibo in time. This paper aims to classify and monitor Weibo public opinion through Convolutional Neural Network (CNN). Firstly, the data is cleaned up and a vocabulary is built. Then the model of the convolutional neural network is built, including the embedding layer, the convolution layer, the pooling layer and the fully connected layer. Finally, the data is predicted and classified by the Softmax function. The experimental results show that the model can effectively classify and predict the Weibo public opinion, which is a certain improvement compared with the traditional machine learning algorithm.
引用
收藏
页码：127 / 130
页数：4
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