R5 model for case-based reasoning

被引：137

作者：

Finnie, G ^{[1
]}

Sun, ZH ^{[1
]}

机构：

[1] Bond Univ, Sch Informat Technol, Gold Coast 4229, Australia

来源：

KNOWLEDGE-BASED SYSTEMS | 2003年 / 16卷 / 01期

基金：

澳大利亚研究理事会;

关键词：

case-based reasoning; similarity; partition; case base building;

D O I：

10.1016/S0950-7051(02)00053-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper reviews some existing models of case-based reasoning (CBR) such as the R-4 model of CBR and proposes a R-5 model, in which repartition, retrieve, reuse, revise and retain are the main tasks for the CBR process. The original idea behind this model is that case base building is an important part of CBR and the case base can be built based on partitioning of the possible world of problems and solutions. It argues that the proposed R-5 model is a new approach to using similarity-based reasoning to unify case base building, case retrieval, and case adaptation, and therefore facilitates the development of CBR with applications. (C) 2003 Elsevier Science B.V. All rights reserved.

引用

页码：59 / 65

页数：7

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