Application of a 3NN+1 based CBR system to segmentation of the notebook computers market
Case-based reasoning system (CBR) has been widely applied to the issue of market segmentation. Most of previous studies focused on dividing customers into two groups. Consequently, traditional voting method used for two groups in CBR would become inappropriate when one would like to divide customers into three groups through some segmentation variable. In this paper, a new voting method called 3NN+1 is proposed to bridge the gap. To make the inference of the 3NN+1 based CBR system more efficient, the features and instances (or cases) for reasoning is selected simultaneously by means of genetic algorithms. This new system is applied to a real case of notebook market to demonstrate its usefulness for market segmentation. From the results of the real case, it shows that the system would be valuable to enterprises, when dividing customers into three groups in compliance with their purchasing behaviors for developing marketing strategies.
case-based reasoning market segmentation genetic algorithms simultaneous selection of features and instances