Applying machine learning techniques for email reply prediction

Taiwo Ayodele, Shikun Zhou, Rinat Khusainov

Research output: Chapter in Book/Report/Published conference proceedingChapterpeer-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 publicationProceedings of the World Congress on Engineering 2009
EditorsS.I. Ao, Len Gelman, David W.L. Hukins, Andrew Hunter, A.M. Korsunsky
PublisherNewswood Limited
Number of pages6
ISBN (Print)9789881701251
Publication statusPublished - 1 Jul 2009
Externally publishedYes
EventWorld Congress on Engineering 2009 - London, United Kingdom
Duration: 1 Jul 20093 Jul 2009


ConferenceWorld Congress on Engineering 2009
Abbreviated titleWCE
Country/TerritoryUnited Kingdom
Internet address

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