Evolving email clustering method for email grouping: a machine learning approach

Taiwo Ayodele*, Shikun Zhou, Rinat Khusainov

*Corresponding author for this work

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

Abstract

This paper presents the design and implementation of a new system to manage email messages using email evolving clustering method with unsupervised learning approach to group emails base on activities found in the email messages, namely email grouping. Users spend a lot of time reading, replying and organizing their emails. To help users organize their email messages, we propose a new framework to help organise and prioritize email better. The goal is to provide highly structured and prioritized emails, thus saving the user from browsing through each email one by one and help to save time.

Original languageEnglish
Title of host publication2009 Second International Conference on the Applications of Digital Information and Web Technologies
PublisherInstitute of Electrical and Electronics Engineers
Pages357-362
Number of pages6
ISBN (Electronic)9781424444571
ISBN (Print)9781424444564
DOIs
Publication statusPublished - 2 Oct 2009
Event2nd International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2009 - London, United Kingdom
Duration: 4 Aug 20096 Aug 2009

Conference

Conference2nd International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2009
Country/TerritoryUnited Kingdom
CityLondon
Period4/08/096/08/09

Keywords

  • clustering methods
  • machine learning
  • postal services
  • electrochemical machining
  • design engineering
  • engineering management
  • unsupervised learning
  • organizing
  • mission critical systems
  • telephony

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