中南民族大学学报（自然科学版）2018，Vol.37Issue(1)：138-143,6.
基于卷积神经网络的中文新闻文本分类
Text Classification of Chinese News Based on Convolutional Neural Network
摘要
Abstract
The classical convolutional neural network text classification model only focuses on the global features, without taking into account the local features. To solve this problem,the attention mechanism is introduced to extract keywords from the text. In this way,the global features and local features are combined together,which makes the feature representation of the text richer. Experimental results show that the text categorization model of Convolutional Neural Network is better than the traditional machine learning methods. Compared with the classical text classification model, after introducing attention mechanism,the performance of Convolutional Neural Network classification model has been improved.关键词
自然语言处理/深度学习/卷积神经网络/注意力机制/文本分类Key words
natural language processing/deep learning/Convolutional Neural Network/attention mechanism/text classification分类
信息技术与安全科学引用本文复制引用
蓝雯飞,徐蔚,王涛..基于卷积神经网络的中文新闻文本分类[J].中南民族大学学报（自然科学版）,2018,37(1):138-143,6.基金项目
国家自然科学基金资助项目(61379059) （61379059）
