An error probability estimation of the document classification using Markov model

Manabu Kobayashi*, Hiroshi Ninomiya, Toshiyasu Matsushima, Shigeichi Hirasawa

*この研究の対応する著者

研究成果: Conference contribution

抄録

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.

本文言語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
国/地域United States
CityHonolulu, HI
Period12/10/2812/10/31

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 情報システム

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