Intelligent email summarisation system (IESS)

Taiwo Ayodele*, Shikun Zhou, Rinat Khusainov

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Many email users, especially business men, managers and academician receive many email messages that require sorting out within a short period of time. While most mail summarisation applications allow dialogue structure of emails, users to summarise messages into percentages or numbers of sentences. In practice this task tends to be tedious and solutions available today often require programming skills on the part of the email users. The users define rules for summarising messages. For each message, the user must first decide which message is most important. Then, the user must inform the mail summariser of that choice by selecting the appropriate icon or menu item from among what is typically a set of several dozen choices. The combined effort of choosing a message and conveying that choice to the application often discourages users from summarising their mails, resulting in unmanageable inboxes that contain hundreds or even thousands of un-précised and unnecessary messages. Intelligent email summarisation system (IESS), encourages users to have summative messages by simplifying the content of the mail. Using unsupervised machine learning techniques in combination with automated word and phrases modeller to intelligently provide a précis summary of each email messages is developed to reduce the burden of email users.

Original languageEnglish
Title of host publication2010 International Conference on Information Society (i-Society)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9780956426338
ISBN (Print)9781457718236
Publication statusPublished - 15 Sept 2011
Event2010 International Conference on Information Society - London, United Kingdom
Duration: 28 Jun 201030 Jun 2010


Conference2010 International Conference on Information Society
Abbreviated titlei-Society 2010
Country/TerritoryUnited Kingdom


  • electronic mail
  • postal services
  • machine learning
  • humans
  • feature extraction


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