AI-Based Automated Framework for Online Apparel Product Detail Pages Generation 


Vol. 15,  No. 1, pp. 1-11, Jan.  2026
10.3745/TKIPS.2026.15.1.1


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  Abstract

Product Detail Pages (PDPs) involves significant manual efforts, resulting in high costs, time consumption, dependence on skilled labor, and various technical limitations. To address these challenges, this study proposes an AI-based integrated automation framework for PDPs generation. The proposed framework standardizes PDPs into four areas and applies automation algorithms, particularly to the ‘product feature appeal’ and ‘optional photo arrangement’ sections, thereby enhancing overall page generation efficiency. In the ‘product feature appeal’ section, a large language model pre-trained on fashion domain data is used to automatically generate text. This framework also adopt model that is trained to automatically select images that matches the generated text. In the ‘photo arrangement by product options’ section, images are segmented into foreground and background, and embeddings are generated. Hierarchical clustering, reflecting both foreground and background information, is then used to group similar images. By analyzing frame types, images in the clusters are arranged to display optional products and model images naturally. The proposed framework is validated using real-world data. The results demonstrate that the proposed method excels in text generation, image clustering, and image arrangement consistency. Furthermore, evaluations by online shopping mall operators, related experts, and consumers shows that quality level of generated PDP is comparable to manual work. This study presents the first automation framework that comprehensively addresses both text and image aspects, thereby proving its applicability and scalability in the fashion industry.

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[IEEE Style]

J. Y. Shim, J. Park, Y. Choi, "AI-Based Automated Framework for Online Apparel Product Detail Pages Generation," The Transactions of the Korea Information Processing Society, vol. 15, no. 1, pp. 1-11, 2026. DOI: 10.3745/TKIPS.2026.15.1.1.

[ACM Style]

Joo Yong Shim, JiYoon Park, and Yerim Choi. 2026. AI-Based Automated Framework for Online Apparel Product Detail Pages Generation. The Transactions of the Korea Information Processing Society, 15, 1, (2026), 1-11. DOI: 10.3745/TKIPS.2026.15.1.1.

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