Applying machine learning algorithms for email management

Taiwo Ayodele; Shikun Zhou

doi:10.1109/ICPCA.2008.4783606

Applying machine learning algorithms for email management

Taiwo Ayodele^*
, Shikun Zhou

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings of the 3rd International Conference on Pervasive Computing and Applications, ICPCA 2008
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	339-344
Number of pages	6
ISBN (Print)	9781424420209
DOIs	https://doi.org/10.1109/ICPCA.2008.4783606
Publication status	Published - 13 Feb 2009
Event	2008 3rd International Conference on Pervasive Computing and Applications - Alexandria, Egypt Duration: 6 Oct 2008 → 8 Oct 2008

Conference

Conference	2008 3rd International Conference on Pervasive Computing and Applications
Abbreviated title	ICPCA08
Country/Territory	Egypt
City	Alexandria
Period	6/10/08 → 8/10/08

Keywords

Email grouping
Emails
Reply prediction
Summarization
Unsupervised learning

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10.1109/ICPCA.2008.4783606

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@inproceedings{4b1b508d708e4169806dcafc36cd2199,

title = "Applying machine learning algorithms for email management",

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 = "Email grouping, Emails, Reply prediction, Summarization, Unsupervised learning",

author = "Taiwo Ayodele and Shikun Zhou",

year = "2009",

month = feb,

day = "13",

doi = "10.1109/ICPCA.2008.4783606",

language = "English",

isbn = "9781424420209",

pages = "339--344",

booktitle = "Proceedings of the 3rd International Conference on Pervasive Computing and Applications, ICPCA 2008",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2008 3rd International Conference on Pervasive Computing and Applications, ICPCA08 ; Conference date: 06-10-2008 Through 08-10-2008",

}

Ayodele, T & Zhou, S 2009, Applying machine learning algorithms for email management. in Proceedings of the 3rd International Conference on Pervasive Computing and Applications, ICPCA 2008. Institute of Electrical and Electronics Engineers Inc., pp. 339-344, 2008 3rd International Conference on Pervasive Computing and Applications, Alexandria, Egypt, 6/10/08. https://doi.org/10.1109/ICPCA.2008.4783606

TY - GEN

T1 - Applying machine learning algorithms for email management

AU - Ayodele, Taiwo

AU - Zhou, Shikun

PY - 2009/2/13

Y1 - 2009/2/13

N2 - 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.

AB - 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.

KW - Email grouping

KW - Emails

KW - Reply prediction

KW - Summarization

KW - Unsupervised learning

UR - https://www.scopus.com/pages/publications/64049088441

U2 - 10.1109/ICPCA.2008.4783606

DO - 10.1109/ICPCA.2008.4783606

M3 - Conference contribution

AN - SCOPUS:64049088441

SN - 9781424420209

SP - 339

EP - 344

BT - Proceedings of the 3rd International Conference on Pervasive Computing and Applications, ICPCA 2008

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2008 3rd International Conference on Pervasive Computing and Applications

Y2 - 6 October 2008 through 8 October 2008

ER -

Applying machine learning algorithms for email management

Abstract

Conference

Keywords

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