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

• 作者: Cunfang Li Nan Ma Nuan Cao Rui Ma ShaoHua Zhang Taohong Zhang
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: Convolutional NEURAL network(CNN) TEXT FEATURE EXTRACTION Class operation
• 年，卷（期）: 2017,（1）
• 页码范围: 119-121
• 页数: 3页
• 分类号: C5

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.