Using case-based reasoning and knowledge mapping to solve multiple-condition problems
by Mu-Jung Huang; Mu-Yen Chen; Meng-Yu Lin
International Journal of Social and Humanistic Computing (IJSHC), Vol. 2, No. 3/4, 2017

Abstract: Most current case-based reasoning (CBR) systems are designed for solving single-condition problems. However, there are multiple-condition problems (i.e., those involving several different problem conditions, such as personal computer [PC] problems) that also need specific solutions. Thus, this paper attempts to integrate CBR concepts with knowledge mapping in a CBR system designed to solve multiple-condition problems. This study makes three critical contributions: 1) it adopts a user-oriented approach to measuring case similarity and allows the user to select from a list of category features to characterise the new problem; 2) it presents a knowledge mapping algorithm suitable for applying the knowledge of experts to the proposed problems; 3) it uses a prototype to demonstrate how smoothly the proposed approach can solve the target PC problems. Our results indicate that a CBR system with a knowledge mapping approach is suitable for solving multiple-condition problems.

Online publication date: Mon, 19-Jun-2017

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