• DocumentCode
    2141477
  • Title

    Statistical Evaluation of Measure and Distance on Document Classification Problems in Text Mining

  • Author

    Goto, Masayuki ; Ishida, Takashi ; Hirasawa, Shigeichi

  • Author_Institution
    Musashi Inst. of Technol., Yokohama
  • fYear
    2007
  • fDate
    16-19 Oct. 2007
  • Firstpage
    674
  • Lastpage
    673
  • Abstract
    This paper discusses the document classification problems in text mining from the viewpoint of asymptotic statistical analysis. By formulation of statistical hypotheses test which is specified as a problem of text mining, some interesting properties can be visualized. In the problem of text mining, the several heuristics are applied to practical analysis because of its experimental effectiveness in many case studies. The theoretical explanation about the performance of text mining techniques is required and this approach will give us very clear idea. The distance measure in word vector space is used to classify the documents. In this paper, the performance of distance measure is also analized from the new viewpoint of asymptotic analysis.
  • Keywords
    classification; data mining; statistical testing; text analysis; asymptotic statistical analysis; distance measure; document classification; statistical evaluation; statistical hypotheses test; text mining; word vector space; Extraterrestrial measurements; Frequency measurement; H infinity control; Information retrieval; Information technology; Parametric statistics; Performance analysis; Testing; Text categorization; Text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on
  • Conference_Location
    Aizu-Wakamatsu, Fukushima
  • Print_ISBN
    978-0-7695-2983-7
  • Type

    conf

  • DOI
    10.1109/CIT.2007.171
  • Filename
    4385162