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Paper Abstract and Keywords
Presentation 2025-06-02 09:15
Reduction of Individual Differences in Aesthetic Preferences via Principal Component Analysis of a Kernel Ridge Regression Set -- A Study on Rectangle Aspect Ratios --
Sho Tanaka (OECU), Hideaki Ishibashi (Kyushu Inst. of Tech.), Masashi Komori (OECU) HCS2025-21 HIP2025-21
Abstract (in Japanese) (See Japanese page) 
(in English) Humans can be viewed as possessing their own internal utility functions that transform continuous physical inputs into a psychological quantity referred to as ``beauty.'' In this study, we call such internal utility functions ``Kansei.'' We attempt to summarize individual differences in Kansei and to visualize both their uniqueness and commonality by applying principal component analysis (PCA) to a set of kernel ridge regressions. As a case study, we focus on aesthetic evaluations of rectangle aspect ratios.

20 undergraduate students were asked to rate the aesthetic quality of rectangles with various aspect ratios using a seven-point Likert scale. From these ratings, each person's utility function was estimated via kernel ridge regression, after which PCA was applied to the resulting set of regression coefficients.

The results suggest that the first factor reflects a preference for elongated rectangles, the second factor corresponds to a preference for the golden ratio, and the third factor relates to whether or not there is a preference for square shapes. These findings demonstrate the effectiveness of applying PCA on a set of kernel ridge regressions in Kansei research.
Keyword (in Japanese) (See Japanese page) 
(in English) Kernel Ridge Regression / Functional Pricipal Component Analysis / Kansei / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 46, HCS2025-21, pp. 101-104, June 2025.
Paper # HCS2025-21 
Date of Issue 2025-05-25 (HCS, HIP) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF HCS2025-21 HIP2025-21

Conference Information
Committee HIP HCS HI-SIGCOASTER  
Conference Date 2025-06-01 - 2025-06-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication Enhancing, Human Communications, and Human Information Processing 
Paper Information
Registration To HCS 
Conference Code 2025-06-HIP-HCS-SIGCOASTER 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reduction of Individual Differences in Aesthetic Preferences via Principal Component Analysis of a Kernel Ridge Regression Set 
Sub Title (in English) A Study on Rectangle Aspect Ratios 
Keyword(1) Kernel Ridge Regression  
Keyword(2) Functional Pricipal Component Analysis  
Keyword(3) Kansei  
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1st Author's Name Sho Tanaka  
1st Author's Affiliation Osaka Electro-Communication University (OECU)
2nd Author's Name Hideaki Ishibashi  
2nd Author's Affiliation Kyushu Institute of Technology (Kyushu Inst. of Tech.)
3rd Author's Name Masashi Komori  
3rd Author's Affiliation Osaka Electro-Communication University (OECU)
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Speaker Author-1 
Date Time 2025-06-02 09:15:00 
Presentation Time 18 minutes 
Registration for HCS 
Paper # HCS2025-21, HIP2025-21 
Volume (vol) vol.125 
Number (no) no.46(HCS), no.47(HIP) 
Page pp.101-104 
#Pages 4 
Date of Issue 2025-05-25 (HCS, HIP) 

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