Using case-based reasoning and knowledge mapping to solve multiple-condition problems Online publication date: Mon, 19-Jun-2017
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
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Social and Humanistic Computing (IJSHC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org