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OCR 및 프롬프트 엔지니어링 기반 SEO 최적화 방안 연구: e커머스 상품 상세페이지 적용 사례Enhancing SEO through OCR and Prompt Engineering Techniques: A Case of E-commerce Product Detail Pages
- Other Titles
- Enhancing SEO through OCR and Prompt Engineering Techniques: A Case of E-commerce Product Detail Pages
- Issue Date
- Jun-2025
- Publisher
- 한국정보시스템학회
- Keywords
- Optical Character Recognition (OCR); Prompt Engineering; Search Engine Optimization (SEO); Product Detail Page; E-commerce
- Citation
- 정보시스템연구, v.34, no.2, pp 27 - 43
- Pages
- 17
- Indexed
- KCI
- Journal Title
- 정보시스템연구
- Volume
- 34
- Number
- 2
- Start Page
- 27
- End Page
- 43
- ISSN
- 1229-8476
2733-8770
- Abstract
- Purpose This study addresses the difficulties faced by small business owners and solo entrepreneurs in implementing effective SEO strategies due to limited technical knowledge and resources. It proposes a practical method using OCR and prompt engineering to enhance search visibility in image-heavy e-commerce product pages. Design/methodology/approach The proposed method extracts text from product images using Optical Character Recognition (OCR) and restructures it into SEO-friendly HTML through ChatGPT-based prompt engineering. The method was applied to a real e-commerce platform and compared with conventional image-only product pages in terms of search engine exposure and user traffic. Findings The results show that the framework significantly improves online visibility and user inflow. This approach provides a low-cost, accessible SEO solution for small sellers, contributing to their competitiveness in the expanding digital marketplace.
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Related Researcher
- Yoon, Sang Hyeak
- Dongguk Business School (Department of Management Information System)