Optimization Design of a Webpage Based on Kansei Engineering

Abstract

Webpage design has become an important component affecting user satisfaction when they surf the Internet. Interface designers are struggling to improve the quality of user experience by designing webpages that meet users’ emotional needs. An optimization design method of webpage interface is proposed in this study based on Kansei engineering theory, and a job-hunting website homepage is taken as the research example. After determining the materials, the semantic differential (SD) method is used to extract user-centered emotional dimensions, and the key design factors of homepages’ appearance are acquired. Next, based on the obtained semantic differential evaluation data, back propagation neural network (BPNN) is conducted to identify quantitative relations between key design factors and emotional dimensions. Finally, genetic algorithm (GA) is employed to search for a near-optimal design. The proposed method is helpful to design webpages that can satisfy participants’ emotions. It can also be used in a variety of design cases.

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