Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design

Feng Zhao, Jianxin Roger Jiao, Dirk Schaefer, Songlin Chen

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

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
Original languageEnglish
Pages (from-to)031010-1 - 031010-9
Number of pages9
JournalJournal of Computing and Information Science in Engineering
Volume10
Issue number3
Early online date3 Sep 2010
DOIs
Publication statusPublished - 2010

Fingerprint

Logistics
Cabs (truck)
Trucks

Keywords

  • Engineering Design

Cite this

Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design. / Zhao, Feng; Jiao, Jianxin Roger; Schaefer, Dirk; Chen, Songlin.

In: Journal of Computing and Information Science in Engineering, Vol. 10, No. 3, 2010, p. 031010-1 - 031010-9.

Research output: Contribution to journalArticle

Zhao, Feng ; Jiao, Jianxin Roger ; Schaefer, Dirk ; Chen, Songlin. / Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design. In: Journal of Computing and Information Science in Engineering. 2010 ; Vol. 10, No. 3. pp. 031010-1 - 031010-9.
@article{ae4ea830f0a241c7b068101d8a179f23,
title = "Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design",
abstract = "Emotional design entails a bidirectional affective mapping process between affectiveneeds in the customer domain and design elements in the designer domain. To leverageboth affective and engineering concerns, this paper proposes a hybrid association miningand refinement (AMR) system to support affective mapping decisions. Rough set and Koptimal rule discovery techniques are applied to identify hidden relations underlyingforward affective mapping. A rule refinement measure is formulated in terms of affectivequality. Ordinal logistic regression (OLR) is derived to model backward affective mapping.Based on conjoint analysis, a weighted OLR model is developed as a benchmark ofthe initial OLR model for backward refinement. A case study of truck cab interior designis presented to demonstrate the feasibility and potential of the hybrid AMR system fordecision support to forward and backward affective mapping",
keywords = "Engineering Design",
author = "Feng Zhao and Jiao, {Jianxin Roger} and Dirk Schaefer and Songlin Chen",
year = "2010",
doi = "10.1115/1.3482063",
language = "English",
volume = "10",
pages = "031010--1 -- 031010--9",
journal = "Journal of Computing and Information Science in Engineering",
issn = "1530-9827",
publisher = "American Society of Mechanical Engineers (ASME)",
number = "3",

}

TY - JOUR

T1 - Hybrid Association Mining and Refinement for Affective Mapping in Emotional Design

AU - Zhao, Feng

AU - Jiao, Jianxin Roger

AU - Schaefer, Dirk

AU - Chen, Songlin

PY - 2010

Y1 - 2010

N2 - Emotional design entails a bidirectional affective mapping process between affectiveneeds in the customer domain and design elements in the designer domain. To leverageboth affective and engineering concerns, this paper proposes a hybrid association miningand refinement (AMR) system to support affective mapping decisions. Rough set and Koptimal rule discovery techniques are applied to identify hidden relations underlyingforward affective mapping. A rule refinement measure is formulated in terms of affectivequality. Ordinal logistic regression (OLR) is derived to model backward affective mapping.Based on conjoint analysis, a weighted OLR model is developed as a benchmark ofthe initial OLR model for backward refinement. A case study of truck cab interior designis presented to demonstrate the feasibility and potential of the hybrid AMR system fordecision support to forward and backward affective mapping

AB - Emotional design entails a bidirectional affective mapping process between affectiveneeds in the customer domain and design elements in the designer domain. To leverageboth affective and engineering concerns, this paper proposes a hybrid association miningand refinement (AMR) system to support affective mapping decisions. Rough set and Koptimal rule discovery techniques are applied to identify hidden relations underlyingforward affective mapping. A rule refinement measure is formulated in terms of affectivequality. Ordinal logistic regression (OLR) is derived to model backward affective mapping.Based on conjoint analysis, a weighted OLR model is developed as a benchmark ofthe initial OLR model for backward refinement. A case study of truck cab interior designis presented to demonstrate the feasibility and potential of the hybrid AMR system fordecision support to forward and backward affective mapping

KW - Engineering Design

UR - http://dx.doi.org/10.1115/1.3482063

U2 - 10.1115/1.3482063

DO - 10.1115/1.3482063

M3 - Article

VL - 10

SP - 031010-1 - 031010-9

JO - Journal of Computing and Information Science in Engineering

JF - Journal of Computing and Information Science in Engineering

SN - 1530-9827

IS - 3

ER -