This poster addresses accessibility issues of electronic theses and dissertations (ETDs) in digital libraries (DLs). ETDs are available primarily as PDF files, which present barriers to equitable access, especially for users with visual impairments, cognitive or learning disabilities, or for anyone needing more efficient and effective ways of finding relevant information within these long documents. We propose using AI techniques, including natural language processing (NLP), computer vision, and text analysis, to convert PDFs into machine-readable HTML documents with semantic tags and structure, extracting figures and tables, and generating summaries and keywords. Our goal is to increase the accessibility of ETDs and to make this important scholarship available to a wider audience.

翻译：本海报探讨了数字图书馆中电子学位论文（ETDs）的可访问性问题。ETDs主要以PDF格式提供，这种格式构成了公平访问的障碍，尤其是对于视力障碍、认知或学习障碍的用户，以及任何需要更高效、更有效方式在这些长文档中查找相关信息的用户。我们提出利用人工智能技术，包括自然语言处理（NLP）、计算机视觉和文本分析，将PDF转换为带有语义标签和结构的机器可读HTML文档，提取图表，并生成摘要和关键词。我们的目标是提高ETDs的可访问性，使这些重要的学术成果能够服务于更广泛的受众。