An error probability estimation of the document classification using Markov model

Manabu Kobayashi, Hiroshi Ninomiya, Toshiyasu Matsushima, Shigeichi Hirasawa

研究成果: Conference contribution

抜粋

The document classification problem has been investigated by various techniques, such as a vector space model, a support vector machine, a random forest, and so on. On the other hand, J. Ziv et al. have proposed a document classification method using Ziv-Lempel algorithm to compress the data. Furthermore, the Context-Tree Weighting (CTW) algorithm has been proposed as an outstanding data compression, and for the document classification using the CTW algorithm experimental results have been reported. In this paper, we assume that each document with same category arises from Markov model with same parameters for the document classification. Then we propose an analysis method to estimate a classification error probability for the document with the finite length.

元の言語English
ホスト出版物のタイトル2012 International Symposium on Information Theory and Its Applications, ISITA 2012
ページ717-721
ページ数5
出版物ステータスPublished - 2012 12 1
イベント2012 International Symposium on Information Theory and Its Applications, ISITA 2012 - Honolulu, HI, United States
継続期間: 2012 10 282012 10 31

出版物シリーズ

名前2012 International Symposium on Information Theory and Its Applications, ISITA 2012

Conference

Conference2012 International Symposium on Information Theory and Its Applications, ISITA 2012
United States
Honolulu, HI
期間12/10/2812/10/31

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • これを引用

    Kobayashi, M., Ninomiya, H., Matsushima, T., & Hirasawa, S. (2012). An error probability estimation of the document classification using Markov model. : 2012 International Symposium on Information Theory and Its Applications, ISITA 2012 (pp. 717-721). [6401034] (2012 International Symposium on Information Theory and Its Applications, ISITA 2012).