• DocumentCode
    549429
  • Title

    Email urgency reply prediction

  • Author

    Ayodele, Taiwo ; Shoniregun, Charles A. ; Zhou, Shikun

  • Author_Institution
    Res. Lab., Infonetmedia Ltd., Portsmouth, UK
  • fYear
    2011
  • fDate
    27-29 June 2011
  • Firstpage
    418
  • Lastpage
    422
  • Abstract
    The email urgency reply prediction (EURP) is a way of handling, and determining emails that require imperative reply with respect to time. Over the past few years, email has become the preferred medium of communication for many businesses and individuals. As a growing portion of our lives is captured over email exchanges, the phenomenon of the overcrowded and unmanaged inbox is becoming an increasingly serious impediment to communications and productivity. This research work focuses on the broader goal of providing users with effective applications to determine mails that require urgent replies - the task of urgency reply prediction has a sustainable economic benefits to both private and public sectors.
  • Keywords
    electronic mail; unsupervised learning; EURP; email determination; email handling; email machine learning; email urgency reply prediction; expectation learning; sustainable economic benefits; unsupervised machine learning; Indexes; email machine learning; expectation learning; keyword index; prediction; unsupervised machine learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Society (i-Society), 2011 International Conference on
  • Conference_Location
    London
  • Print_ISBN
    978-1-61284-148-9
  • Type

    conf

  • Filename
    5978483