Rough Set Based Rule Mining for Affective Design

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.

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