AN INVESTIGATION OF VIETNAMESE DOCUMENT CLASSIFICATION

  • Bui Duc Tho Hung Yen University of Technology and Education
  • Nguyen Hoang Diep Hung Yen University of Technology and Education
  • Do Thi Thu Trang Hung Yen University of Technology and Education
  • Nguyen Thi Hai Nang Hung Yen University of Technology and Education
  • Ngo Thanh Huyen Hung Yen University of Technology and Education
  • Minh-Tien Nguyen Hung Yen University of Technology and Education
  • Van-Hau Nguyen Hung Yen University of Technology and Education
Keywords: text classification, neural networks, supervised learning, deep learning

Abstract

Automatic text classification is one of the most interesting task in data mining. This task has to deal with a huge amount of data. Many studies have been investigated for English, however, the investigation of Vietnamese is still an early stage. This paper investigates several text classification methods: Super Vector Machine, Naive Bayes Classification, K-Nearest Neighbors, Multi-layer perceptron, Decision Tree, Random Forest using TF-IDF. The experiments in Vietnamese datasets show that Super Vector Machine and Multi-layer perceptron perform better than the other methods.

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Published
2020-10-12
How to Cite
Bui Duc Tho, Nguyen Hoang Diep, Do Thi Thu Trang, Nguyen Thi Hai Nang, Ngo Thanh Huyen, Minh-Tien Nguyen, & Van-Hau Nguyen. (2020). AN INVESTIGATION OF VIETNAMESE DOCUMENT CLASSIFICATION. UTEHY Journal of Science and Technology, 27, 105-110. Retrieved from https://tapchi.utehy.edu.vn/index.php/jst/article/view/397