rule refinement
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2016 ◽  
pp. 294-328
Author(s):  
Gheorghe Tecuci ◽  
Dorin Marcu ◽  
Mihai Boicu ◽  
David A. Schum
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2010 ◽  
Vol 3 (1-2) ◽  
pp. 588-597 ◽  
Author(s):  
Bin Liu ◽  
Laura Chiticariu ◽  
Vivian Chu ◽  
H. V. Jagadish ◽  
Frederick R. Reiss

Author(s):  
Feng Zhou ◽  
Jianxin Roger Jiao ◽  
Dirk Schaefer ◽  
Songlin Chen

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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