为提升客户对产品的认可度，针对传统概念设计阶段未充分考虑客户感性需求偏好及客户感性需求获取困难的问题，提出一种在线评论数据驱动的客户感性需求识别及向设计特征映射方法。首先，基于形态学分析法，通过构建能量材料信号(Energy Material Signal，EMS)模型试图从产品中发现所有设计特征，并基于在线评论数据从所有设计特征中筛选出用户关注的核心特征;其次，从在线评论数据中提取形容词组成感性词对，以感性词作为中心词并利用词向量技术获得非中心词，基于情感词典，利用所给方法计算产品感性词对的感性评价值;然后，基于数量化理论Ⅰ(Quantitative Theory Ⅰ，QTⅠ)建立客户感性评价与产品设计元素之间的映射模型，并为改进产品设计提供依据;最后，通过实例验证所提方法的可行性和有效性。
Customer emotional needs recognition and mapping to design features based on online comment data driving
In order to improve customer recognition of the product,aiming at the problem that customer's perceptual demand pref-erence and difficulty in obtaining customer demand are not fully considered in the traditional conceptual design stage,a method of customer emotional perceptual needs recognition and mapping to design features by online reviews of product data is proposed.Firstly,based on morphological analysis,try to find all design features from products by building Energy Material Sig-nal(EMS)model,and core features that users were concerned about were screened out from all the design features based on on-line review data.Secondly,adjectives are extracted from the review data to form a perceptual word pair.The perceptual word is used as the head word to obtain the non head word using word vector technology.Based on the emotional dictionary,the perceptu-al score of the product's perceptual word pair is calculated using the given method.Thirdly,based on the quantitative theory Ⅰ,the mapping model between perceptual evaluation and design elements is established,which provides a basis for improving prod-uct design.Finally,the feasibility and effectiveness of the proposed method are verified by an example.
customer emotional needsonline reviewproduct designtext miningkansei engineeringQuantitative Theory Ⅰ(QT Ⅰ)
万方数据
维普
