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Ripple-down rules with censored production rules

Citation

Kim, YS and Compton, P and Kang, BH, Ripple-down rules with censored production rules, Proceedings of the Knowledge Management and Acquisition for Intelligent Systems (PKAW 2012), 5-6 September 2012, Kuching, Malaysia, pp. 175-187. ISBN 978-3-642-32540-3 (2012) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 Springer

DOI: doi:10.1007/978-3-642-32541-0

Abstract

Ripple-Down Rules (RDR) has been successfully used to implement incremental knowledge acquisition systems. Its success largely depends on the organisation of rules, and less attention has been paid to its knowledge repre- sentation scheme. Most RDR used standard production rules and exception rules. With sequential processing, RDR acquires exception rules for a particular rule only after the rule wrongly classifies cases. We propose censored produc- tion rules (CPR), to be used for acquiring exceptions when a new rule is created using censor conditions. This approach is useful when we have a large number of validation cases at hand. We discuss inference and knowledge acquisition al- gorithms and related issues. The approach can be combined with machine learn- ing techniques to acquire censor conditions.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Expert Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
Author:Kang, BH (Professor Byeong Kang)
ID Code:81898
Year Published:2012
Deposited By:Computing and Information Systems
Deposited On:2013-01-10
Last Modified:2015-02-13
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