Proposal of Clustering Method based on Procrustes Analysis

Abstract

Recently, a lot of researches that focus on humans' subjectivity have been reported. In these researches, the SD (Semantic Differential) method is one of the most useful methods to quantify the humans' subjectivity. Some methods to compare individuals' impression using SD data have been proposed. This paper proposes the clustering method based on Orthogonal Procrustes Analysis (OPA). The proposed method can cluster the sets of data points based on the similarity of their structures. Therefore, this method can extract subjects among whom the distributed structures of the SD data are similar. This method enables us to compare the similarity/difference of humans' impression and analyze the relationships among the clusters. This paper applies the proposed method to the data group added arbitrary orthogonalization transformation as a preliminary experiment. This paper shows that the proposed method can form appropriate clusters to the objects with unknown shapes without giving prior knowledge about their shapes.