目的 使食品包装设计能够精准地反映消费者的差异化偏好,响应动态的市场变化,提出一种通过消费者在线评论数据挖掘,获取消费者对食品包装的感性意象,并辅助人工智能精准生成包装设计方案的方法。方法 通过网络爬虫技术获取消费者在线评论数据,提取数据中的形容词,转化为产品感性评价意象词。基于语义差异法,构建产品的感性质量评价量表,运用多元回归分析确认用户对包装设计的偏好。最后将偏好信息转化为生成参数,应用Midjourney生成初步方案供设计师优化和改进。结果 以蜂蜜包装设计为例,应用该方法获取到了8款具有偏好差异的蜂蜜包装设计方案,设计师选择其一继续进行设计深化,并使用NPS净推荐值评估设计方案,且获得了消费者较高的满意度,验证了方法的有效性。结论 该方法能够精准地捕获消费者的差异化偏好,辅助设计人员更有效地使用AIGC工具缩短研发周期,提升设计效率,为食品包装设计的创新提供新的思路和方法。
Abstract
In order to make food packaging design accurately reflect consumers' differentiated preferences and respond to dynamic market changes, the work aims to propose a method to obtain consumers' perceptual images of food packaging through data mining of consumers' online reviews, and assist artificial intelligence to accurately generate packaging design schemes. The online review data of consumers were obtained through web crawler technology, and the adjectives in the data were extracted and transformed into product perceptual evaluation image words. Based on the semantic difference method, the perceptual quality evaluation scale of the product was constructed, and the multiple regression analysis was used to confirm the user's preference for packaging design. Finally, the preference information was transformed into the generation parameters, and the preliminary scheme was generated by Midjourney for designers to optimize and improve. With honey packaging design as an example, eight honey packaging design schemes with preference differences were obtained by this method. Designers selected one of them to continue the design deepening, and used the NPS net recommendation value to evaluate the design scheme, which obtained higher consumer satisfaction and verified the effectiveness of the method. This method enables precise identification of consumers' unique preferences, facilitating designers to leverage AIGC tools more efficiently to expedite the development process, enhance design productivity, and introduce fresh concepts and methodologies for food packaging design innovation.
关键词
在线评论数据挖掘 /
感性评价 /
食品包装设计 /
生成式人工智能（AIGC）辅助设计
Key words
online review data mining /
perceptual evaluation /
food packaging design /
artificial intelligence generated content (AIGC) aided design
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基金
教育部人文社会科学研究一般项目（24YJC760170）; 河北省教育厅科学研究项目（SQ2022036）; 河北省社科基金（HB23YS034）; 河北省等学校科学研究项（BJ2025160）; 河北工业大学基本科研业务费项目（424132031）
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