Document classification method with small training data

Yasunari Maeda, Hideki Yoshida, Toshiyasu Matsushima

研究成果: Conference contribution

抜粋

Document classification is one of important topics in the field of NLP(Natural Language Processing). In our previous research we've proposed a document classification method which minimizes an error rate with reference to a Bayes criterion. But when the number of documents in training data is small, the accuracy of the previous method is low. So in this research we propose a document classification method whose accuracy is higher than the previous method when the number of documents in training data is small.

元の言語English
ホスト出版物のタイトルICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
ページ138-141
ページ数4
出版物ステータスPublished - 2009 12 1
イベントICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
継続期間: 2009 8 182009 8 21

出版物シリーズ

名前ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
Japan
Fukuoka
期間09/8/1809/8/21

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

これを引用

Maeda, Y., Yoshida, H., & Matsushima, T. (2009). Document classification method with small training data. : ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings (pp. 138-141). [5333327] (ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings).