Abstract
Abstract In this paper, we verify an effectiveness of “Kansei rules” to analyze impressions of products. In our previous paper, we have proposed a method for making Kansei rules by using a parallel Genetic Algorithm (GA). The Kansei rules are generated by results of questionnaires. These results determine users’product impressions and help to uncover major factors that affect product’s attractiveness. Therefore, we analyzed appearance of running shoes and investigated the factors that determine particular user preferences. In this paper, we examine to estimate consumer’s overall impression of the product from their response to particular components of unknown questionnaire data by using generated rules. In the experiment, we compared performance of rules by using a parallel GA and by using a fuzzy C4.5 decision tree of our previous study. As a result, we verified the effectiveness of the method by using a parallel GA.
