• DocumentCode
    1895386
  • Title

    Unsupervised email vector space model (UEVSM)

  • Author

    Ayodele, Taiwo

  • Author_Institution
    Dept. of Electron. & Comput. Eng., Univ. of Portsmouth, Portsmouth, UK
  • fYear
    2010
  • fDate
    8-11 Nov. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    There are many challenges of grouping email messages. One of the challenging issues of email message group is to pinpoint when the clustering process accumulates accurate and sufficient information for grouping is archived. In this work, an unsupervised machine learning technique has been developed based on unsupervised clustering method (UCM). The proposed unsupervised clustering method is new and different from other existing UCMs such as: email evolving clustering method.
  • Keywords
    electronic mail; pattern clustering; unsupervised learning; vectors; email message group; unsupervised clustering method; unsupervised email vector space model; unsupervised machine learning technique; Europe; Indexes; Semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Technology and Secured Transactions (ICITST), 2010 International Conference for
  • Conference_Location
    London
  • Print_ISBN
    978-1-4244-8862-9
  • Electronic_ISBN
    978-0-9564263-6-9
  • Type

    conf

  • Filename
    5678093