Applying machine learning techniques for email reply prediction

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    Abstract

    For several years now, email has grown rapidly as the most-used communications tool on the internet. One advantage of the Internet is the ease with which people can communicate online. The popularity of online communication has created an explosion of users who regularly access the internet to connect with others. Many people use email to stay in touch with relatives and friends who live far away geographically. We propose a new framework to help prioritised email better using machine learning techniques; an intelligent email reply prediction system. Our goal is to provide concise, highly structured and prioritised emails, thus saving the user from browsing through thousands of emails and help to reduce time spent on checking and reading email messages.
    Original languageEnglish
    Title of host publicationThe World Congress on Engineering 2009 Volume I
    EditorsS. Ao, L. Gelman, D. Hukins, A. Hunter, A. Korsunsky
    Place of PublicationLondon, UK
    PublisherNewswood Limited
    Pages31-36
    Number of pages6
    Edition2176
    ISBN (Print)9789881701251
    Publication statusPublished - 1 Jul 2009
    EventProceedings of the World Congress on Engineering - London
    Duration: 1 Jul 20093 Jul 2009

    Publication series

    NameLecture Notes in Engineering and Computer Science
    PublisherNewswood Limited
    Number2176

    Conference

    ConferenceProceedings of the World Congress on Engineering
    Period1/07/093/07/09

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