DocumentCode
549429
Title
Email urgency reply prediction
Author
Ayodele, Taiwo ; Shoniregun, Charles A. ; Zhou, Shikun
Author_Institution
Res. Lab., Infonetmedia Ltd., Portsmouth, UK
fYear
2011
fDate
27-29 June 2011
Firstpage
418
Lastpage
422
Abstract
The email urgency reply prediction (EURP) is a way of handling, and determining emails that require imperative reply with respect to time. Over the past few years, email has become the preferred medium of communication for many businesses and individuals. As a growing portion of our lives is captured over email exchanges, the phenomenon of the overcrowded and unmanaged inbox is becoming an increasingly serious impediment to communications and productivity. This research work focuses on the broader goal of providing users with effective applications to determine mails that require urgent replies - the task of urgency reply prediction has a sustainable economic benefits to both private and public sectors.
Keywords
electronic mail; unsupervised learning; EURP; email determination; email handling; email machine learning; email urgency reply prediction; expectation learning; sustainable economic benefits; unsupervised machine learning; Indexes; email machine learning; expectation learning; keyword index; prediction; unsupervised machine learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Society (i-Society), 2011 International Conference on
Conference_Location
London
Print_ISBN
978-1-61284-148-9
Type
conf
Filename
5978483
Link To Document