Author: Lam, Wai-chung Rico
Title: Competence maintenance for case-based reasoning systems
Degree: M.Sc.
Year: 2001
Subject: Case-based reasoning
Data mining
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Department of Computing
Pages: 61 leaves : ill. ; 30 cm
Language: English
Abstract: Recently interest in data mining has focused on the techniques from statistics, machine learning, database technology and high performance computing. Relatively few techniques have been suggested in the literature in relation to the management of the discovered knowledge. The uncontrolled case-base growth in Case-Based Reasoning (CBR) system can cause serious performance problem such as the degrade of the retrieval efficiency and the exist of incorrect or inconsistent cases which are difficult to detect. This has long been identified as a bottleneck in CBR development with many systems either simply using all available cases or relying on an expert to identity key cases. In this project, the focus will be placed on the deletion of the similar cases so that the overall competence and performance of the CBR can be enhanced. The use of Kohonen's network will help to calculate the case density and global competence of the cases. Afterward a case deletion model is suggested which will delete the cases in a case base based on the case density value of a case. Finally we shall evaluate the results of case deletion based on different measurement.
Rights: All rights reserved
Access: restricted access

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