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Applying machine learning techniques for email reply prediction

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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

Documents

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ID: 100175