Electronic Thesis

Electronic theses and dissertations (ETDs) are increasingly studied as a rich source of scholarly data, prompting research into efficient processing and analysis. Current research focuses on improving metadata quality through AI-driven methods, enhancing document summarization and keyword extraction using probabilistic models and submodular functions, and exploring the capabilities and limitations of large language models (LLMs) for tasks like subject heading assignment and text generation. These efforts aim to improve the discoverability, accessibility, and analytical potential of ETDs, impacting both academic research and library science.