• DocumentCode
    3287286
  • Title

    Feature Selection for Document Type Classification

  • Author

    Taghva, Kazem ; Vergara, Jason

  • Author_Institution
    Univ. of Nevada, Las Vegas
  • fYear
    2008
  • fDate
    7-9 April 2008
  • Firstpage
    179
  • Lastpage
    182
  • Abstract
    In this paper, we report on the identification of document type using a k-dependence Bayesian categorization engine. In particular, we show that the use of font and capitalization as features improves precision and recall.
  • Keywords
    Bayes methods; character sets; classification; document handling; capitalization; document type classification; feature selection; font; k-dependence Bayesian categorization engine; Bayesian methods; Computer networks; Data mining; Engines; Information science; Information technology; Mutual information; Optical character recognition software; Text categorization; Training data; OCR; document classification; document type; text categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations, 2008. ITNG 2008. Fifth International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    0-7695-3099-0
  • Type

    conf

  • DOI
    10.1109/ITNG.2008.25
  • Filename
    4492475
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3287286