Subject Heading

Research on subject heading assignment is exploring the use of large language models (LLMs) to automate the process, significantly reducing manual effort in tasks like cataloging electronic theses and assigning Library of Congress Subject Headings (LCSH). Current work focuses on improving the accuracy and completeness of LLM-generated headings, often employing techniques like prompt engineering and leveraging existing topic models such as Non-negative Matrix Factorization (NMF). This automation has the potential to enhance knowledge organization and retrieval across diverse digital archives, improving access to information and facilitating more efficient knowledge management.