Automatic Classification for Vietnamese News

Phan Thi Ha, Nguyen Quynh Chi


This paper proposes an automatic framework to classify Vietnamese news from news sites on the Internet. In this proposed framework, the extracted main content of Vietnamese news is performed automatically by applying the improved performance extraction method from [1]. This information will be classified by using two machine learning methods: Support vector machine and naïve bayesian method. Our experiments implemented with Vietnamese news extracted from some sites showed that the proposed classification framework give acceptable results with a rather high accuracy, leading to applying it to real information systems.


news classification; automatic extraction; support vector machine; naïve bayesian networks

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