• DocumentCode
    456456
  • Title

    A Bayesian Approach for Text Classification

  • Author

    Colace, Francesco ; De Santo, Massimo

  • Author_Institution
    DIIIE, Universitd di Salerno, Fisciano
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1323
  • Lastpage
    1326
  • Abstract
    The continuous increase of digital information requires technologies and techniques that can easily and quickly manage them. One of the most important and hot topic in this field is the introduction of techniques for text classification. The aim of this paper is the design and the implementation of a method for text classification. In particular we used an approach based on the use of Bayesian networks. In order to test our approach we use it on the standard Reuters database. The obtained results are very promising
  • Keywords
    belief networks; classification; text analysis; Bayesian network; Reuters database; text classification; Bayesian methods; Databases; Expert systems; Machine assisted indexing; Probability distribution; Random variables; Technology management; Testing; Text categorization; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies, 2006. ICTTA '06. 2nd
  • Conference_Location
    Damascus
  • Print_ISBN
    0-7803-9521-2
  • Type

    conf

  • DOI
    10.1109/ICTTA.2006.1684572
  • Filename
    1684572