A Kansei mining system for affective design

Affective design has received much attention from both academia and industries. It aims at incorporating customers' affective needs into design elements that deliver customers' affective satisfaction. The main challenge for affective design originates from difficulties in mapping customers' subjective impressions, namely Kansei, to perceptual design elements. This paper intends to develop an explicit decision support to improve the Kansei mapping process by reusing knowledge from past sales records and product specifications. As one of the important applications of data mining, association rule mining lends itself to the discovery of useful patterns associated with the mapping of affective needs. A Kansei mining system is developed to utilize valuable affect information latent in customers' impressions of existing affective designs. The goodness of association rules is evaluated according to their achievements of customers' expectations. Conjoint analysis is applied to measure the expected and achieved utilities of a Kansei mapping relationship. Based on goodness evaluation, mapping rules are further refined to empower the system with useful inference patterns. The system architecture and implementation issues are discussed in detail. An application of Kansei mining to mobile phone affective design is presented.

[1]  M. Wedel,et al.  Market Segmentation: Conceptual and Methodological Foundations , 1997 .

[2]  Don Clausing.  Total quality development : a step-by-step guide to world class concurrent engineering , 1994 .

[3]  A. Eagly,et al.  Attitudes and opinions. , 1978, Annual review of psychology.

[4]  Brian R. Gaines,et al.  Requirements acquisition , 1996, Softw. Eng. J..

[5]  Peter C. Wright,et al.  Funology: from usability to enjoyment , 2005 .

[6]  正人 宇治川.  生きる喜びをデザインするという新しい学問の誕生 : International Conference on Affective Human Factors Designの報告(会員フォーラム) , 2001 .

[7]  Martin G Helander,et al.  Hedonomics—affective human factors design , 2003, Ergonomics.

[8]  Bodil Karlsson,et al.  Using semantic environment description as a tool to evaluate car interiors , 2003, Ergonomics.

[9]  Neil A. M. Maiden,et al.  ACRE: selecting methods for requirements acquisition , 1996, Softw. Eng. J..

[10]  Yukihiro Matsubara,et al.  An automatic builder for a Kansei Engineering expert system using self-organizing neural networks , 1995 .

[11]  Oya Demirbilek,et al.  Product design, semantics and emotional response , 2003, Ergonomics.

[12]  C. Osgood,et al.  The Measurement of Meaning , 1958 .

[13]  Nigel Cross,et al.  Engineering Design Methods: Strategies for Product Design , 1994 .

[14]  N. Bianchi-Berthouze,et al.  Kansei-mining: identifying visual impressions as patterns in images , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[15]  Alison McKay,et al.  Requirements management: a representation scheme for product specifications , 2001, Comput. Aided Des..

[16]  Kristin L. Wood,et al.  Functional Interdependence and Product Similarity Based on Customer Needs , 1999 .

[17]  Paul E. Green,et al.  Models and Heuristics for Product Line Selection , 1985 .

[18]  G. Kelly.  The Psychology of Personal Constructs , 2020 .

[19]  Mary Jo Bitner,et al.  Services Marketing: Integrating Customer Focus Across the Firm , 1996 .

[20]  Philip S. Yu,et al.  Data Mining: An Overview from a Database Perspective , 1996, IEEE Trans. Knowl. Data Eng..

[21]  Paul E. Green,et al.  Additive Decomposition of Perceptions Data Via Conjoint Analysis , 1978 .

[22]  Tzu-Chuen Lu,et al.  Mining association rules procedure to support on-line recommendation by customers and products fragmentation , 2001, Expert Syst. Appl..

[23]  Rakesh Agarwal,et al.  Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.

[24]  Halimahtun M. Khalid,et al.  Affective and Pleasurable Design , 2006 .

[25]  Mitchell M. Tseng,et al.  Computer-Aided Requirement Management for Product Definition: A Methodology and Implementation , 1998 .

[26]  松原 行宏,et al.  感性工学(Kansei Engineering) , 1998 .

[27]  M. Lucertini,et al.  Modelling the Innovation: Communications, Automation and Information Systems, Proceedings of the IFIP TC7 Conference on Modelling the Innovation: Communications, Automation and Information Systems, Rome, Italy, 21-23 March, 1990 , 1990, Modelling the Innovation.

[28]  Gavriel Salvendy,et al.  Handbook of Human Factors and Ergonomics , 2005 .

[29]  Shirley A. Lewis.  ILLUMINATIVE INCIDENT ANALYSIS , 1976 .

[30]  M. Mead,et al.  Coming of Age in Samoa , 1929 .

[31]  Yukihiro Matsubara,et al.  Hybrid kansei engineering system and design support , 1997 .

[32]  Thorsten Blecker,et al.  An Advisory System for Customers’ Objective Needs Elicitation in Mass Customization , 2003 .

[33]  Li Pheng Khoo,et al.  A Radial Basis Function Neural Network Multicultural Factors Evaluation Engine For Product Concept Development , 2001, Expert Syst. J. Knowl. Eng..

[34]  Mildred L. G. Shaw.  Recent advances in personal construct technology , 1981 .

[35]  Shuichi Fukuda,et al.  Prioritizing the customer's requirements by AHP for concurrent design , 1993 .

[36]  Halimahtun M. Khalid,et al.  A Framework for Affective Customer Needs in Product Design , 2002 .

[37]  A. D. Bitta,et al.  Consumer Behavior: Concepts and Applications , 1979 .

[38]  Todd Barlow,et al.  Structured Brainstorming: A Method for Collecting User Requirements , 1993 .

[39]  B. Kahn,et al.  Variety for sale: Mass customization or mass confusion? , 1998 .

[40]  Li Pheng Khoo,et al.  A strategy for acquiring customer requirement patterns using laddering technique and ART2 neural network , 2002, Adv. Eng. Informatics.

[41]  M. Rouse,et al.  The Customer Centric Enterprise : Advances in Mass Customization and Personalization , 2003 .

[42]  Li Pheng Khoo,et al.  An integrated approach to the elicitation of customer requirements for engineering design using picture sorts and fuzzy evaluation , 2002, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[43]  Richard Y. K. Fung,et al.  Product design resources optimization using a non-linear fuzzy quality function deployment model , 2002 .

[44]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[45]  D. Anderson,et al.  Predicting Preferences for New Product Configurations: a High-Tech Example , 1990, Modelling the Innovation.

[46]  K. Seltman.  Marketing for management. , 2004, Marketing health services.

[47]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[48]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.