Meng-Jin Wu, Tzu-Yuan Fu, Yao-Chung Chang, Chia-Wei Lee
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A Study on Natural Language Processing Classified News
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%.
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