眼动结合用户集群的苗族文化感性工学模型构建研究

Study on Eye-Movement Combined with User Clusters for Miao Cultural Kansei Engineering Model Construction

摘要: 为解决传统用户感性需求映射存在模糊性和不确定性的问题，对此提出了一种眼动结合用户集群的苗族文化感性工学模型构建方法。首先，获取苗族纹样和文化意象，运用造型分析法解构纹样形态，基于K-modes建立用户集群；其次，开展面向集群用户意象–纹样认知眼动实验；再者，基于KNN算法识别被试所属集群，基于集群眼动数据遴选苗族文化符码样本关键造型类目；最后，引入PLS多元回归分析，获得集群意象和苗族文化符码的相关性回归系数，实现集群用户文化意象–符码映射模型构建。基于此模型能够快速获取用户偏好的苗族符码造型，有效地促进苗族文创产品的创新设计与开发。

Abstract: In order to solve the problem of ambiguity and uncertainty of traditional user perceptual demand mapping, an eye-movement combined with user clusters is proposed to build a Kansei engineering model of Miao culture. First, we obtain Miao motifs and cultural imagery, deconstruct the motif morphology using modeling analysis, and establish user clusters based on K-modes; second, we conduct eye-movement experiments on image-motion perception for cluster users; further, we identify the clusters to which the subjects belong based on KNN algorithm, and select the key modeling categories of Miao cultural symbols samples based on cluster eye-movement data; finally, PLS multiple regression analysis was applied to obtain the cluster image and the correlation regression coefficients of Miao cultural codes to realize the construction of the cluster user cultural image-code mapping model. Based on this model, we can quickly obtain the user’s preferred Miao symbolic shapes and effectively promote the innovative design and development of Miao cultural and creative products.