AI-CSD模型驱动提示词优化的AIGC辅助文创产品设计研究

田雪棠; 毛咸

doi:10.19798/j.cnki.2096-6946.2026.01.009

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工业工程设计 ›› 2026, Vol. 8 ›› Issue (1) : 100-112. DOI: 10.19798/j.cnki.2096-6946.2026.01.009

设计创新与应用

AI-CSD模型驱动提示词优化的AIGC辅助文创产品设计研究

田雪棠^*, 毛咸

作者信息 +

AIGC-Assisted Cultural and Creative Product Design Based on the AI-CSD Model for Prompt Optimization

TIAN Xuetang^*, MAO Xian

Author information +

文章历史 +

摘要

为解决AIGC辅助文创产品设计过程中文化表达模糊、提示词结构不明等问题,基于皮尔斯符号现象范畴理论,提出AIGC-文化符号描述（AIGC-Culture Semiotics Description,AI-CSD）模型,结合KJ法对文化符号词库进行聚类,归纳总结文创产品设计方向,以河南淮扬泥泥狗文化为例,运用Midjourney平台开展多轮图像生成实验,并通过李克特量表对生成结果进行文化一致性与设计满意度评估;同时引入文化符号识别率（R_s）等客观指标对生成结果进行交叉验证,进一步增强评价结论的可验证性与说服力。研究表明,AI-CSD模型与KJ法联合应用能有效优化提示词结构,提升AIGC生成文创产品图像的文化表达准确性与一致性,促进文创产品设计方向探索,为AIGC文创产品设计提供理论支撑与方法创新。

Abstract

To address the challenges of ambiguous cultural expression and unclear prompt structures in AIGC-assisted cultural and creative product design, the work aims to propose the AIGC-Culture Semiotics Description (AI-CSD) model based on Peirce's phenomenological categories and triadic semiotic theory. The model integrates Peirce's semiotic framework with the KJ method to cluster the cultural symbol lexicon and synthesize design orientations for cultural and creative products. With the "Ni Ni Dog" cultural heritage in Huaiyang, Henan as a case study, multiple rounds of image-generation experiments are conducted on the Midjourney platform. The generated images are evaluated through the Likert-scale assessment focusing on cultural consistency and design satisfaction. In addition, objective indicators such as the cultural symbol recognition rate (R_s) are introduced for cross-validation, thereby enhancing the verifiability and robustness of the evaluation results. The findings indicate that the combined application of the AI-CSD model and KJ method can effectively optimize prompt structures, enhance the accuracy and consistency of cultural representation in AI-generated content, and promote the exploration of design directions for cultural and creative products, providing theoretical support and methodological innovation for AIGC-assisted cultural and creative product design.

导出引用

田雪棠, 毛咸. AI-CSD模型驱动提示词优化的AIGC辅助文创产品设计研究[J]. 工业工程设计. 2026, 8(1): 100-112 https://doi.org/10.19798/j.cnki.2096-6946.2026.01.009

TIAN Xuetang, MAO Xian. AIGC-Assisted Cultural and Creative Product Design Based on the AI-CSD Model for Prompt Optimization[J]. Industrial & Engineering Design. 2026, 8(1): 100-112 https://doi.org/10.19798/j.cnki.2096-6946.2026.01.009

中图分类号： J524

参考文献

[1] 范凌,李丹,卓京港,等. 人工智能赋能传统工艺美术传承研究:以金山农民画为例[J]. 装饰,2022(7):94-98.
[2] 周琪瑶,赵卫东. 生成式人工智能辅助下文创设计方法研究综述[J]. 包装工程,2025,46(4):121-133.
[3] 腾讯研究院. AIGC发展趋势报告2023[EB/OL]. (2023-02-24)[2025-04-08]. https://cloud.tencent.com/developer/article/2223837.
[4] AZZOLA A. FIGOLI F. RAMPINO L.Generative AI in the Design Process: A Journey through Image Generation for Concept Ideation[M]. Milano: FrancoAngeli,2025.
[5] ZHANG L,HU F.Analysis of the Design of Cultural and Creative Products from the Perspective of Regional Culture[J]. IOP Conference Series:Materials Science and Engineering,2019,573(1):012071.
[6] 张安华,马璐璐,吕少卿,等. 陕西旬邑库淑兰剪纸符号智能创新设计应用[J]. 包装工程,2025,46(10):292-305.
[7] 宋玉,钱晓松,彭凌钰,等. AIGC中式美学文创设计研究[J]. 包装工程,2023,44(24):1-8.
[8] YIN H,ZHANG Z P,LIU Y Y.The Exploration of Integrating the Midjourney Artificial Intelligence Generated Content Tool into Design Systems to Direct Designers towards Future-Oriented Innovation[J]. Systems,2023,11(12):566.
[9] NAYAK S,BHATIA M,ZHANG X F,et al. CulturalFrames:Assessing Cultural Expectation Alignment in Text-to-Image Models and Evaluation Metrics[EB/OL]. (2025-06-10)[2025-07-11] 2025:arXiv:2506.08835. https://arxiv.org/abs/2506.08835.
[10] 祝昆皓,徐秀峰,齐瑞文. AI赋能地方文创产品设计路径研究——以江西地方文化为例[J]. 包装工程,2024,45(S1):191-197.
[11] 曾真. 设计中的人与人工智能协同创意研究[D]. 上海:同济大学,2022.
[12] JEONG S,CHOI I,YUN Y,et al. Culture-TRIP:Culturally-Aware Text-to-Image Generation with Iterative Prompt Refinement[EB/OL]. (2025-06-10)[2025-07-11] 2025:arXiv:2502.16902. https://arxiv.org/abs/2502.16902.
[13] 胡飞,杨瑞. 设计符号与产品语意——理论、方法及应用[M]. 2版. 北京:中国建筑工业出版社,2012:27-28.
[14] 皮尔斯. 皮尔斯:论符号[M]. 赵星植,译. 成都: 四川大学出版社,2014:8-14.
[15] 李白杨,白云,詹希旎,等. 人工智能生成内容(AIGC)的技术特征与形态演进[J]. 图书情报知识,2023,40(1):66-74.
[16] 赵文强,臧欣慈. 皮尔斯符号学视域下AIGC对文创产品的设计探索[J]. 包装工程,2024,45(10):116-126.
[17] 张祎,于东玖. 基于皮尔斯符号学的潍坊风筝文创产品设计研究[J]. 包装工程,2024,45(14):253-262.
[18] SCUPIN R.The KJ Method:A Technique for Analyzing Data Derived from Japanese Ethnology[J]. Human Organization,1997,56(2):233-237.
[19] 曹鑫,鲁红雷. 文化创意产品的设计启发式开发研究[J]. 工业设计,2023(6):55-57.
[20] 解天龙. 基于KJ法及KANO模型的图书馆文创产品设计与开发[J]. 晋图学刊,2023(3):55-63.
[21] 刘文良,马雪寒. 基于KJ-KANO模型的亲子家居文创产品设计研究[J]. 家具与室内装饰,2024,31(3):72-77.
[22] QIU X,ZHONG M L,LIN Y X,et al.Application and Research of Hakka Building Codes in Cultural and Creative Product Design[J]. Innovation on Design and Culture,2023,2(1):8-14.
[23] 吴小龙,肖静华,吴记. 当创意遇到智能:人与AI协同的产品创新案例研究[J]. 管理世界,2023,39(5):112-126.
[24] OPPENLAENDER J,LINDER R,SILVENNOINEN J. Prompting AI Art:An Investigation into the Creative Skill of Prompt Engineering[EB/OL]. (2023-03-13)[2025-08-11]. https://arxiv.org/abs/2303.13534.
[25] CROPLEY D.Is Artificial Intelligence More Creative than Humans?:ChatGPT and the Divergent Association Task[J]. Learning Letters,2023,2:13.
[26] 孙磊,刘正宏. 淮阳泥泥狗[M]. 北京:中国轻工业出版社,2017:10-14.
[27] 行摄中原. 淮阳“泥泥狗”,千年“活化石”[EB/OL].(2022-03-06)[2025-05-07]. https://www.thepaper.cn/newsDetail_forward_16977944.
[28] 阎建华. 特色手工艺品泥泥狗[EB/OL]. ( 2022-03-06)[2025-05-07]. https://www.quanjing.com/imgbuy/QJ9134714352.html.
[29] 贝丽尔·马克龙. 设计中的智慧思维[M]. 北京:中国摄影出版社,2018:212-213.
[30] AKVERDI C,BAYKAL G E.Generative AI Tools in Design Fields:Opportunities and Challenges in the Ideation Process[C]//Adjunct Proceedings of the 2024 Nordic Conference on Human-Computer Interaction. Uppsala:ACM,2024:1-5.
[31] PASCALE S, CARLAND J, CARLAND J A.A Comparative Analysis of Two Concept Evaluation Methodsfor New Product Development Projects[J]. Project Management Journal, 1997,28(4):47-52.
[32] 贾怀鹏. 淮阳泥泥狗的故事——意象及其审美潜能[M]. 北京:新华出版社,2018:24.
[33] 郭梦迪. AIGC赋能当代海派版画融入文创设计的应用研究[J]. 包装工程,2025,46(10):396-405.