DocumentCode :
3540177
Title :
Evolving email clustering method for email grouping: A machine learning approach
Author :
Ayodele, Taiwo ; Zhou, Shikun ; Khusainov, Rinat
Author_Institution :
Dept. of Electron. & Comput. Eng., Univ. of Portsmouth, Portsmouth, UK
fYear :
2009
fDate :
4-6 Aug. 2009
Firstpage :
357
Lastpage :
362
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.
Keywords :
electronic mail; pattern clustering; unsupervised learning; email clustering method; email grouping; email messages; machine learning approach; unsupervised learning approach; Clustering methods; Design engineering; Electrochemical machining; Engineering management; Machine learning; Mission critical systems; Organizing; Postal services; Telephony; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the
Conference_Location :
London
Print_ISBN :
978-1-4244-4456-4
Electronic_ISBN :
978-1-4244-4457-1
Type :
conf
DOI :
10.1109/ICADIWT.2009.5273973
Filename :
5273973
Link To Document :
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