• DocumentCode
    2956461
  • Title

    Automated Text Binary Classification Using Machine Learning Approach

  • Author

    Holts, Alberto ; Riquelme, Claudio ; Alfaro, Rodrigo

  • Author_Institution
    Escuela de Ing. Inf., Pontificia Univ. Catolica de Valparaiso, Valparaíso, Chile
  • fYear
    2010
  • fDate
    15-19 Nov. 2010
  • Firstpage
    212
  • Lastpage
    217
  • Abstract
    The increased number of documents in digital format available on the Web and its useful information for different purposes entail an essential need to organize them. However, this task must be automated in order to save costs and manpower. In the community research, the main approach to face this problem is based on the application of machine learning techniques. This article studies the main machine learning approaches to reach an automated text classification.
  • Keywords
    Internet; learning (artificial intelligence); pattern classification; text analysis; automated text binary classification; digital document; machine learning; Artificial neural networks; Electronic mail; Machine learning; Niobium; Support vector machines; Testing; Training; Machine learning; Text classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Chilean Computer Science Society (SCCC), 2010 XXIX International Conference of the
  • Conference_Location
    Antofagasta
  • ISSN
    1522-4902
  • Print_ISBN
    978-1-4577-0073-6
  • Electronic_ISBN
    1522-4902
  • Type

    conf

  • DOI
    10.1109/SCCC.2010.30
  • Filename
    5750517