HITZER, Eckhard    Senior Associate Professor    Division of Arts and Sciences, College of Liberal Arts, International Christian University
Language	English
Publication Date	2008
Type	Research Paper (International Conference Proceedings)
Peer Review	With peer review
Title	Clustering of Questionnaire Based on Features Extracted by Geometric Algebra
Contribution Type	Joint Work
Journal	Proc. Joint 4th Int. Conf. on Soft Comp. and Intel. Sys., and 9th Int. Symp. on Adv. Intel. Sys.
Journal Type	Japan
Volume, Issue, Pages	pp.798-803
Author and coauthor	HITZER Eckhard, M. T. Pham, K. Tachibana, T. Yoshikawa, T. Furuhashi
Details	Clustering is one of the most useful methods to understand similarity among data. However, most conventional clustering methods do not pay sufficient attention to geometric properties of data. Geometric algebra (GA) is a generalization of complex numbers and of quaternions, and it is able to describe spatial objects and relations between them. In this study we introduce GA to systematically extract geometric features from data. We propose a new clustering method by using various geometric features extracted with GA. We apply the proposed method to clarification of human impressions of a product. In the field of marketing, companies often carry out a questionnaire on consumers for grasping their impressions. Analyzing consumers through the obtained evaluation data enables us to know the tendency of the market and to find problems and/or to make hypotheses that are useful for the development of products. Finally, we discuss clustering results of a questionnaire with/without GA.