用AI让古籍手稿变可搜可读，提升历史文献数字体验
Making History Readable
- 部署定制AI代理实现手写体识别与文本提取
- 通过大模型生成摘要，使复杂文档更易理解
- 聚焦信件、报纸和地图三类史料，提升可检索性
弗吉尼亚理工大学图书馆数字平台（VTUL DLP）收录了大量具有历史与文化价值的数字资料，涵盖手写信件、报纸及地形图等，内容常含复杂版式、褪色图像和难以辨识的手写文字，给在线访问带来挑战。为此，我们将在工作流中集成AI技术，将数字对象中的文本转化为机器可读格式。通过定制化AI代理完成手写识别、文本提取，并利用大语言模型（LLMs）进行内容摘要。本海报展示三个代表性收藏：手写信件、地方报纸与数字化地形图，分别分析其数据难点并提出对应解决方案。整体方法旨在提升用户对历史资料的搜索效率与导航体验。
原文摘要 · Abstract (English)
The Virginia Tech University Libraries (VTUL) Digital Library Platform (DLP) hosts digital collections that offer our users access to a wide variety of documents of historical and cultural importance. These collections are not only of academic importance but also provide our users with a glance at local historical events. Our DLP contains collections comprising digital objects featuring complex layouts, faded imagery, and hard-to-read handwritten text, which makes providing online access to these materials challenging. To address these issues, we integrate AI into our DLP workflow and convert the text in the digital objects into a machine-readable format. To enhance the user experience with our historical collections, we use custom AI agents for handwriting recognition, text extraction, and large language models (LLMs) for summarization. This poster highlights three collections focusing on handwritten letters, newspapers, and digitized topographic maps. We discuss the challenges with each collection and detail our approaches to address them. Our proposed methods aim to enhance the user experience by making the contents in these collections easier to search and navigate.
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