Interface Agents that Learn: An investigation of Learning Issues in a Mail Agent Interface
Payne, Terry R. and Edwards, Peter, Trappl, Robert (ed.) (1997) Interface Agents that Learn: An investigation of Learning Issues in a Mail Agent Interface. Applied Artificial Intelligence, 11, (1), 1-32.
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In recent years, interface agents have been developed to assist users with various tasks. Some systems employ machine learning techniques to allow the agent to adapt to the user's changing requirements. With the increase in the volume of data on the internet, agents have emerged that are able to monitor and learn from their users to identify topics of interest. One such agent, described here, has been developed to filter mail messages. We examine the issues involved in constructing an autonomous interface agent that employs a learning component, and explore the use of two different learning techniques in this context.
|Keywords:||agent mail interface machine learning rule induction nearest neighbour|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science
|Date Deposited:||29 Jan 2003|
|Last Modified:||11 Aug 2012 00:04|
|Contributors:||Payne, Terry R. (Author)
Edwards, Peter (Author)
Trappl, Robert (Editor)
|Further Information:||Google Scholar|
|ISI Citation Count:||31|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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