Abstract
Recently, study on individuality of humans' subjectivity has been emphasized in the field of Kansei engineering. This paper presents a clustering method for Kansei evaluation data considering subjects' individuality. This paper defines two indexes for clustering of subjects based on their data obtained by Semantic Differential (SD) method. These indexes are quantified by the residuals and the amount of transformation in applying the Orthogonal Procrustes Analysis between the averaged SD evaluation data and the individual ones. This paper employs images of laptop computers as the objects of the evaluation by SD method. This paper shows that averaging SD evaluation data leads to loss of the individuality in the data and that the proposed method is effective in clustering of SD evaluation data for the cluster analysis.
