Learning Email Filtering Rules with Magi - A Mail Agent Interface
Learning Email Filtering Rules with Magi - A Mail Agent Interface
As the volume of data on the Internet increases the need for better tools to handle this flood of data is also growing. Interface agents are tools which are designed to aid the user in using various applications. This project describes the development of an agent which employs machine learning techniques to discover rules for filtering email. It explains how the agent observes the user in handling mail and how these observations are used to help automate this task. The agent is then evaluated, through testing, to examine whether such a tool can be useful as a personal assistant. A description of existing work is given, along with the design rationale, and a number of future extensions are suggested.
Payne, T.R.
e0956864-a64d-4333-b63b-e0dc4e8008b3
1994
Payne, T.R.
e0956864-a64d-4333-b63b-e0dc4e8008b3
Payne, T.R.
(1994)
Learning Email Filtering Rules with Magi - A Mail Agent Interface.
University of Aberdeen, Department of Computing Science, Masters Thesis.
Record type:
Thesis
(Masters)
Abstract
As the volume of data on the Internet increases the need for better tools to handle this flood of data is also growing. Interface agents are tools which are designed to aid the user in using various applications. This project describes the development of an agent which employs machine learning techniques to discover rules for filtering email. It explains how the agent observes the user in handling mail and how these observations are used to help automate this task. The agent is then evaluated, through testing, to examine whether such a tool can be useful as a personal assistant. A description of existing work is given, along with the design rationale, and a number of future extensions are suggested.
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msc_thesis.pdf
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Published date: 1994
Organisations:
Electronics & Computer Science
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Local EPrints ID: 257789
URI: http://eprints.soton.ac.uk/id/eprint/257789
PURE UUID: 5a9e1e71-c481-41ce-8351-e7856cd58923
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Date deposited: 24 Jun 2003
Last modified: 14 Mar 2024 06:03
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Author:
T.R. Payne
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