| 孙利,张硕,覃忠志,吴俭涛,李江南.评论数据驱动的产品情感满意度预测模型构建[J].包装工程,2023,44(6):42-51. |
| 评论数据驱动的产品情感满意度预测模型构建 |
| Construction of Product Emotional Satisfaction Prediction Model Driven by Comment Data |
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| DOI：10.19554/j.cnki.1001-3563.2023.06.005 |
| 中文关键词: 产品设计 康养辅具产品 多维设计要素 情感满意度 用户评论数据 |
| 英文关键词: product design health care assistive device multidimensional design elements emotional satisfaction user comment data |
| 基金项目:国家社科基金艺术学项目(22BG125) |
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| 中文摘要: |
| 目的 针对康养辅具产品多维设计要素与用户情感满意度的复杂映射问题，提出了一种基于评论数据的产品情感满意度预测模型。方法 首先爬取样本评论数据，并利用LDA模型构建产品多维设计要素空间，同时对样本进行要素编码;其次对各样本对应的评论数据进行情感满意度分析，以获得情感满意度分值;最后通过BP神经网络构建情感满意度预测模型，结合K-fold交叉验证法测试模型可靠性。结果 以康养辅具电动轮椅为例，通过30个样本数据集交叉验证后得到预测值与期望值的均方误差值为0.044 1，表明该预测模型精度良好，具有较高的可靠性。最后利用该预测模型对104 976个随机组合方案进行情感满意度计算，得出电动轮椅最佳组合方案。结论 基于用户评论数据构建的产品情感满意度预测模型，能够有效建立产品多维设计要素与情感满意度间的匹配关系，辅助设计人员快速识别出用户情感满意度较高的多维设计要素组合，提高了设计方案决策的科学性。 |
| 英文摘要: |
| The work aims to propose a prediction model of product emotional satisfaction based on comment data aiming at the complex mapping problem between multi-dimensional design elements and user emotional satisfaction of health care assistive devices. Firstly, the comment data of samples were crawled, the multi-dimensional element space of products was constructed by LDA model and the elements of the samples were coded. Secondly, the emotional satisfaction of the comment data corresponding to each sample was analyzed to obtain the emotional satisfaction score. Finally, the emotional satisfaction prediction model was constructed by BP neural network, and the reliability of the model was tested by K-fold cross-validation method. With the electric wheelchair as an example, the mean square error between the predicted value and the expected value was 0.044 1 after cross-validation of 30 sample data sets, which showed that the prediction model had good accuracy and high reliability. Next, the emotional satisfaction of 104 976 random combination schemes was calculated by the prediction model, and the best combination scheme of electric wheelchair was obtained. The prediction model of product emotional satisfaction based on user comment data can effectively establish the matching relationship between multi-dimensional design elements and emotional satisfaction, assist designers to quickly identify the combination of multi-dimensional design elements with high user emotional satisfaction, and improve the scientific decision-making of design schemes. |
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