An Automatic Document Classification with Bayesian Learning

베이지안 학습을 이용한 문서의 자동분류

  • Kim, Jin-Sang (School of Computer and Electronics Engineering, Keimyung University) ;
  • Shin, Yang-Kyu (School of Information Science, Kyungsan University)
  • 김진상 (계명대학교 컴퓨터 전자공학부) ;
  • 신양규 (경산대학교 정보과학부)
  • Published : 2000.04.30


As the number of online documents increases enormously with the expansion of information technology, the importance of automatic document classification is greatly enlarged. In this paper, an automatic document classification method is investigated and applied to UseNet 20 newsgroup articles to test its efficacy. The classification system uses Naive Bayes classification algorithm and the experimental result shows that a randomly selected newsgroup arcicle can be classified into its own category over 77% accuracy.


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