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Research Papers

Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design

[+] Author and Article Information
Feng Zhou

 Georgia Institute of Technology, Atlanta, GA 30332-0405Feng.zhou@gatech.edu

Jianxin Roger Jiao1

 Georgia Institute of Technology, Atlanta, GA 30332-0405roger.jiao@me.gatech.edu

Dirk Schaefer

 Georgia Institute of Technology, Atlanta, GA 30332-0405dirk.schaefer@me.gatech.edu

Songlin Chen

 Nanyang Technological University, Singapore 639798, Singaporesonglin@ntu.edu.sg

1

Corresponding author.

J. Comput. Inf. Sci. Eng 10(3), 031010 (Sep 03, 2010) (9 pages) doi:10.1115/1.3482063 History: Received July 10, 2009; Revised July 07, 2010; Published September 03, 2010; Online September 03, 2010

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 K 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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Copyright © 2010 by American Society of Mechanical Engineers
Topics: Design , Mining
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References

Figures

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Figure 1

Bidirectional affective mapping

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Figure 2

Truck cab interior design

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Figure 3

System architecture of hybrid AMR

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Figure 4

Dendrogram of affective descriptor clustering

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Figure 5

Box plot of design element weights

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Figure 6

Visualization of forward association rules

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Figure 7

Visualization of backward association for affect cool

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