Text Feature Extraction and Classification Based on Convolutional Neural Network (CNN)

被引：2

作者：

Zhang, Taohong ^{[1
,2
]}

Li, Cunfang ^{[1
,2
]}

Cao, Nuan ^{[1
]}

Ma, Rui ^{[1
,2
]}

Zhang, ShaoHua ^{[1
]}

Ma, Nan ^{[3
]}

机构：

[1] Univ Sci & Technol Beijing, Beijing, Peoples R China

[2] Beijing Key Lab Knowledge Engn Mat Sci, Beijing, Peoples R China

[3] Beijing Union Univ, Inst Robot, Beijing, Peoples R China

来源：

DATA SCIENCE, PT 1 | 2017年 / 727卷

关键词：

Convolutional neural network (CNN); Text feature extraction; Class operation;

D O I：

10.1007/978-981-10-6385-5_40

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the high-speed development of the Internet, a growing number of Internet users like giving their subjective comments in the BBS, blog and shopping website. These comments contains critics' attitudes, emotions, views and other information. Using these information reasonablely can help understand the social public opinion and make a timely response and help dealer to improve quality and service of products and make consumers know merchandise. This paper mainly discusses using convolutional neural network (CNN) for the operation of the text feature extraction. The concrete realization are discussed. Then combining with other text classifier make class operation. The experiment result shows the effectiveness of the method which is proposed in this paper.

引用

页码：472 / 485

页数：14

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