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

Taiwo Ayodele, Shikun Zhou

    Research output: Contribution to journalArticlepeer-review

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    Abstract

    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.
    Original languageEnglish
    Pages (from-to)143-151
    Number of pages9
    JournalJournal of Engineering and Technology Research
    Volume1
    Issue number7
    Publication statusPublished - Oct 2009

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