DocumentCode :
2735660
Title :
Applying Machine learning Algorithms for Email Management
Author :
Ayodele, Taiwo ; Zhou, Shikun
Author_Institution :
Dept. of Electron. & Comput. Eng., Univ. of Portsmouth, Portsmouth
Volume :
1
fYear :
2008
fDate :
6-8 Oct. 2008
Firstpage :
339
Lastpage :
344
Abstract :
This paper presents the design and implementation of a new system to predict whether email received require a reply, group emails and summarize email messages. The system uses not only subjects and headers fields but also content of email messages to classify emails based on users´ activities and generate summaries of each incoming message with unsupervised learning approach. Our framework tackles the problem of email overload, congestion, difficulties in prioritizing and difficulties in finding previously archived messages in the mail box.
Keywords :
electronic mail; learning (artificial intelligence); email management; email overload; group emails; machine learning algorithms; summarize email messages; unsupervised learning; Algorithm design and analysis; Business communication; Costs; Design engineering; Engineering management; Frequency; Machine learning algorithms; Postal services; Productivity; Unsupervised learning; email grouping; emails; reply prediction; summarization; unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
Conference_Location :
Alexandria
Print_ISBN :
978-1-4244-2020-9
Electronic_ISBN :
978-1-4244-2021-6
Type :
conf
DOI :
10.1109/ICPCA.2008.4783606
Filename :
4783606
Link To Document :
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