A Study on Natural Language Processing Classified News

Meng-Jin Wu, Tzu-Yuan Fu, Yao-Chung Chang, Chia-Wei Lee
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引用次数: 2

Abstract

In recent years, since the Artificial Intelligence (AI) grows up, the machine has better judgment then the human. In this paper, we used Artificial Intelligence to train computer such that it can classify news according to the content of the news. When the category of news did not mark or flag error, the computer can quickly mark the correct news category to reduce the cost and time of human resource. Furthermore, we can build a news classification system for social networks. The system can classify the news from different news media. We used web crawler, data preprocessing, Jieba and NLP to train the computer. After many times to trainings, a large amount of training data, the experimental results show that the accuracy rate of news classification is 97.43%.
分类新闻的自然语言处理研究
近年来,随着人工智能(AI)的发展,机器的判断能力已经超过了人类。在本文中,我们使用人工智能对计算机进行训练,使其能够根据新闻的内容对新闻进行分类。当新闻类别没有标记或标记错误时,计算机可以快速标记正确的新闻类别,以减少人力资源的成本和时间。进一步,我们可以建立一个面向社交网络的新闻分类系统。该系统可以对来自不同新闻媒体的新闻进行分类。我们使用网络爬虫、数据预处理、Jieba和NLP对计算机进行训练。经过多次对大量训练数据进行训练,实验结果表明,新闻分类准确率为97.43%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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