From Preserving Newspapers to Preserving News: An Exploration of AI-Enhanced Preservation of Chinese Historical Newspapers : Long Paper - iPRES 2025 - Wellington, New Zealand / Te Whanganui-a-Tara, Aotearoa
Abstract
Historical newspapers comprehensively document various aspects of society, economic, cultural, educational, and daily life, serving as an indispensable medium for historical research and the understanding of societal transformation. This study proposes an AI-based framework for the recognition and structured processing of Chinese historical newspaper articles. The framework encompasses article region segmentation, identification of article titles and body text, and enhanced content representation. Experimental results demonstrate that annotation methods incorporating visual modifiers significantly improve model performance. The YOLOv10-based segmentation model accurately identifies article regions, while the detection model effectively distinguishes article titles and body text. By integrating with Optical Character Recognition (OCR) and large language models, the proposed framework enables automatic content structuring and summary generation, thereby substantially enhancing the readability and retrievability of historical newspapers. This work offers strong support for digital preservation, digital humanities research, and intelligent information retrieval.Details
- Creators
- Naishuai Zhang
- Institutions
- Date
- 2025-09-01 00:00:00 +0000
- Keywords
- digital humanities
- Publication Type
- paper
- License
- http://creativecommons.org/licenses/by-sa/4.0/
- Download
- 691510 bytes