Modern Manufacturing Engineering ›› 2024, Vol. 521 ›› Issue (2): 16-23.doi: 10.16731/j.cnki.1671-3133.2024.02.003

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Customer emotional needs recognition and mapping to design features based on online comment data driving

CAI Chuang, CUI Huatao, TAO Kaibo, FANG Junwei   

  1. School of Mechanical Engineering, Hefei University of Technology, Hefei 230009,China
  • Received:2023-04-21 Online:2024-02-18 Published:2024-05-29

Abstract: In order to improve customer recognition of the product, aiming at the problem that customer′s perceptual demand preference 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 Signal (EMS) model, and core features that users were concerned about were screened out from all the design features based on online 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 perceptual 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 product design. Finally, the feasibility and effectiveness of the proposed method are verified by an example.

Key words: customer emotional needs, online review, product design, text mining, kansei engineering, Quantitative Theory Ⅰ (QT Ⅰ)

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