Basser Seminar Series
The Intelligent-Electronic Mail Sorter
Dr Eric McCreath
Australian
National University
Wednesday 10 May 2006, 4-5pm
Basser
Conference Room (Madsen Building, Room G92)
Abstract |
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The first part of this presentation
aims to bring together research that relates to the email project we
(Judy Kay, Liz Crawford and myself) have been involved in over the
last 5 years. Sorting email messages into folders is an important
task for a vast number of computer users. The
iems(Intelligent-Electronic Mail Sorter) project is focused on
improving the way users interact with email managers. In this
presentation I will discuss how combining learnt and hand crafted
rules can improve the overall performance of the system. Also I will
present a composite rule learner that classifies mail by combining an
instance based approach with an approach that constructs a general
explicit description. We show that this approach improves
classification erformance. Furthermore, this combined approach
produces understandable and concise classification rules that users
can scrutinize allowing them to maintain a sense of control.
The
second part of this presentation will overview the new email
management system that is being developed and released. I will
present research directions that will be considered. In particular we
wish to consider how other work-flow activities may be combined into
an email manager. An example of this is combining a "todo list"
into an email manager. This would enable associations between
messages and todo items and hence provide a uniform interface for
handling this information. Another aspect I wish to explore on this
new email manager is learning when messages are important then
presenting these important messages to the user.
Speaker's biography |
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Eric McCreath completed his Ph.D. degree in 1999 from the University of New South Wales. This was on research involving Inductive Logic Programming(ILP) which is a sub-field of Machine Learning. As part of his PhD thesis Dr McCreath derived a Bayesian heuristic for finding the most probable hypothesis in a very general framework that allows noisy data and fixed example size. He joined the Basser Department of Computer Science(now the School of Information Technologies) at Sydney University in 1999 and then in 2001 he joined the Department of Computer Science at the Australian National University. Dr McCreath currently holds a lecturing position at the ANU. Recently Dr McCreath has collaborated with Judy Kay from the University of Sydney investigating the application of machine learning techniques in categorizing email within a user's inbox. More recently Dr McCreath has been supervising Robert Bridle during his PhD and together they have investigated novel approach for applying machine learning to improve mobile phone interfaces.