TRANSFERRING CASE KNOWLEDGE TO ADAPTATION KNOWLEDGE: AN APPROACH FOR CASE-BASE MAINTENANCE

摘要

In this article we propose a case-base maintenance methodology based on the idea of transferring knowledge between knowledge containers in a case-based reasoning(CBR) system. A machine-learning technique, fuzzy decision-tree induction, is used to transform the case knowledge to adaptation knowl- edge. By learning the more sophisticated fuzzy adaptation knowledge, many of the redundant cases can be removed.