Emotional design entails a bidirectional affective mapping process between affective needs in the customer domain and design elements in the designer domain. To leverage both affective and engineering concerns, this paper proposes a hybrid association mining and refinement (AMR) system to support affective mapping decisions. Rough set and optimal rule discovery techniques are applied to identify hidden relations underlying forward affective mapping. A rule refinement measure is formulated in terms of affective quality. Ordinal logistic regression (OLR) is derived to model backward affective mapping. Based on conjoint analysis, a weighted OLR model is developed as a benchmark of the initial OLR model for backward refinement. A case study of truck cab interior design is presented to demonstrate the feasibility and potential of the hybrid AMR system for decision support to forward and backward affective mapping.
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September 2010
Research Papers
Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design
Songlin Chen
Songlin Chen
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Feng Zhou
Jianxin Roger Jiao
Dirk Schaefer
Songlin Chen
J. Comput. Inf. Sci. Eng. Sep 2010, 10(3): 031010 (9 pages)
Published Online: September 3, 2010
Article history
Received:
July 10, 2009
Revised:
July 7, 2010
Online:
September 3, 2010
Published:
September 3, 2010
Citation
Zhou, F., Jiao, J. R., Schaefer, D., and Chen, S. (September 3, 2010). "Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design." ASME. J. Comput. Inf. Sci. Eng. September 2010; 10(3): 031010. https://doi.org/10.1115/1.3482063
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