• DocumentCode
    2922964
  • Title

    E-Classifier: A bi-lingual email classification system

  • Author

    Fe´ar, Nouf Al ; Turki, Einas Al ; Zaid, Asma Al ; Duwais, Mashael Al ; Sheddi, Mona Al ; Khamees, Nora Al ; Drees, Nouf Al

  • Author_Institution
    Information Technology department, King Saud University Riyadh, Saudi Arabia
  • Volume
    2
  • fYear
    2008
  • fDate
    26-28 Aug. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In organizations, a large amount of information exchanges using emails. Therefore, it is important to use text mining to discover knowledge from these unstructured emails. Automatic email classification considered as one of important applications in text mining. It is the process of assigning a text email to one or more predefined classes based on their content. This paper focuses on classifying Arabic and English emails. Since Arabic language is highly inflectional and derivational language, this makes text mining a complex task. In our approach, we first preprocessed data using stemming natural language processing technique. Then, we used machine learning algorithm to classify emails. We ran an experiment on our approach using real data sets.
  • Keywords
    Information technology; Machine learning algorithms; Natural language processing; Natural languages; Organizing; Personnel; Radio access networks; System testing; Text categorization; Text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology, 2008. ITSim 2008. International Symposium on
  • Conference_Location
    Kuala Lumpur, Malaysia
  • Print_ISBN
    978-1-4244-2327-9
  • Electronic_ISBN
    978-1-4244-2328-6
  • Type

    conf

  • DOI
    10.1109/ITSIM.2008.4631707
  • Filename
    4631707