Rough Set Based Rule Mining for Affective Design

DS 58-9: Proceedings of ICED 09, the 17th International Conference on Engineering Design, Vol. 9, Human Behavior in Design, Palo Alto, CA, USA, 24.-27.08.2009

Year: 2009
Editor: Norell Bergendahl, M.; Grimheden, M.; Leifer, L.; Skogstad, P.; Lindemann, U.
Author: Zhou, Feng; Jiao, Roger Jianxin; Schaefer, Dirk; Chen, Songlin
Series: ICED
Section: Human Behavior in Design
Page(s): 245-254


Affective design plays an important role in the development of products and services towards high value-added customer satisfaction. The main challenge for affective design is identified as how to translate affective customer needs into design elements. Towards this end, this paper formulates this problem as a rule mining process from the customer domain to the designer domain and proposes a rough set based K-optimal rule discovery method. A rule importance measure, taking rule semantics into account, is used to evaluate and refine the generated rules. A case study of truck cab interior design is also presented to illustrate the potential of the proposed method.

Keywords: Rule mining, affective design, rough set, K-optimal rule discovery


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