Applying machine learning algorithms for email management

Taiwo Ayodele; Shikun Zhou

doi:10.1109/ICPCA.2008.4783606

Applying machine learning algorithms for email management

Research output: Chapter in Book/Report/Published conference proceeding › Conference contribution › peer-review

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	2008 Third International Conference on Pervasive Computing and Applications
Publisher	IEEE
Pages	339-344
Number of pages	6
ISBN (Print)	978-1-4244-2020-9
DOIs	https://doi.org/10.1109/ICPCA.2008.4783606
Publication status	Published - 6 Oct 2008
Externally published	Yes
Event	Third International Conference on Pervasive Computing and Applications (ICPCA 2008) - Alexandria, Egypt Duration: 6 Oct 2008 → 8 Oct 2008

Conference

Conference	Third International Conference on Pervasive Computing and Applications (ICPCA 2008)
Abbreviated title	ICPCA
Country/Territory	Egypt
City	Alexandria
Period	6/10/08 → 8/10/08

Access to Document

10.1109/ICPCA.2008.4783606

Cite this

@inproceedings{c39348f7ce3f40d88415cf7e52571634,

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.",

author = "Taiwo Ayodele and Shikun Zhou",

year = "2008",

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doi = "10.1109/ICPCA.2008.4783606",

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pages = "339--344",

booktitle = "2008 Third International Conference on Pervasive Computing and Applications",

publisher = "IEEE",

note = "Third International Conference on Pervasive Computing and Applications (ICPCA 2008), ICPCA ; Conference date: 06-10-2008 Through 08-10-2008",

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AU - Ayodele, Taiwo

AU - Zhou, Shikun

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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.

U2 - 10.1109/ICPCA.2008.4783606

DO - 10.1109/ICPCA.2008.4783606

M3 - Conference contribution

SN - 978-1-4244-2020-9

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EP - 344

BT - 2008 Third International Conference on Pervasive Computing and Applications

PB - IEEE

T2 - Third International Conference on Pervasive Computing and Applications (ICPCA 2008)

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