Journal of
Engineering and Technology Research

  • Abbreviation: J. Eng. Technol. Res.
  • Language: English
  • ISSN: 2006-9790
  • DOI: 10.5897/JETR
  • Start Year: 2009
  • Published Articles: 198

Full Length Research Paper

Applying machine learning techniques for e-mail management: Solution with intelligent e-mail reply prediction

Taiwo Ayodele and Shikun Zhou
Department of Electronics and Computer Engineering, University of Portsmouth, United Kingdom.
Email: [email protected]

  •  Accepted: 17 August 2009
  •  Published: 31 October 2009



In today’s world, much of our communication is done via e-mail. Many companies and internet users now view e-mail as one of their most critical personal and business applications and would experience serious consequences if their e-mail messages could not be available or experience high volume of messages which lead to congestions, overloads and limited storage space coupled with un-organized e-mail messages. A few years ago, the means of communication are via letter by post, telegraph, fax, couriers to mention a few but now the focus has changed to a faster means of obtaining quick responses and faster ways of communication, e-mails. We propose a new framework to help organised and prioritized e-mail better; e-mail reply prediction. The goal is to provide concise, highly structured and prioritized e-mails, thus saving the user from browsing through each email one by one and help to save time.


Key words: E-mail reply prediction, e-mail messages, interrogative words, requires reply, questions.