Experience with Rule Induction and k-Nearest Neighbour Methods for Interface Agents that Learn


Payne, Terry R., Edwards, Peter and Green, Claire L., Rammamoorthy, C.V., Wah, Benjamin, Bastani, Farokh B. and Spooner, David (eds.) (1997) Experience with Rule Induction and k-Nearest Neighbour Methods for Interface Agents that Learn. IEEE Transactions on Knowledge and Data Engineering, 9, (2), 329-335.

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Description/Abstract

Interface Agents are being developed to assist users with a variety of tasks. To perform effectively, such agents need knowledge of user preferences. An agent architecture has been developed which observes a user performing tasks, and identifies features which can be used as training data by a learning algorithm. Using the learned profile, an agent can give advice to the user on dealing with new situations. The architecture has been applied to two different information filtering domains: classifying incoming mail messages (Magi) and identifying interesting USENET news articles (UNA). This paper describes the architecture and examines the results of experimentation with different learning algorithms and different feature extraction strategies within these domains.

Item Type: Article
ISSNs: 1041-4347
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science
ePrint ID: 257258
Date Deposited: 29 Jan 2003
Last Modified: 27 Mar 2014 19:59
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/257258

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