摘要
目的为了准确识别产品造型的风格,以客车造型为例提出了产品造型风格意象认知空间的构建方法。方法结合自然语言处理和词汇聚类的方法初步提取出常用的造型风格词汇组。借助里克特7点量表对风格描述数据进行离散化表征,并采用主成分分析法提取造型风格的主成分和关键语义特征。在此基础上构建产品造型风格意象的认知空间。结论客车造型风格实例分析结果表明,这种基于主成分分析的造型风格识别方法能够满足客户对产品造型风格需求的描述,较以往主观经验性评价模式具有更强的针对性和指导性。
In order to accurately identify the style of product, it puts forward the method of constructing the cognitive space of the styling image with the example of bus styling. Combined with natural language processing and lexical clus- tering method, the commonly used styling vocabulary is extracted preliminarily. With the help of Richter＇s 7 point scale, the stylistic description data are discretized and the principal components and key semantic features are extracted by principal component analysis （PCA）. On the basis of this, it constructs the cognitive space of product styling image. The results of example show that this style recognition method based on principal component analysis can meet customers＇ demand for product style description. Compared with the previous empirical evaluation model it has stronger pertinence and guidance.
作者
姚干勤
薛澄岐
YAO Gan-qin;XUE Cheng-qi(Institute of Art, Yangzhou Institute of Technology, Yangzhou 225009, China;Institute of Mechanical Engineering, Southeast University, Nanjing 211189, China)
出处
《包装工程》
CAS
北大核心
2018年第12期100-106,共7页
Packaging Engineering
基金
教育部人文社会科学研究规划资助项目(12YJAZH134)
江苏省"十三五"教育科学规划课题重点资助项目(B-a/2016/03/31)
2017年度扬州市职业大学校级重点科研课题(2017RW02)
关键词
造型风格
语义特征
意象认知
主成分
style
semantic feature
image cognition
principal component
