Utilizing Artificial Intelligence for Enhancing Library Cataloging and Metadata Management

Thesis Abstract

Abstract
This thesis explores the utilization of Artificial Intelligence (AI) to enhance library cataloging and metadata management. The advancement of AI technologies presents an opportunity for libraries to improve the efficiency, accuracy, and effectiveness of their cataloging processes. This study aims to investigate the potential benefits, challenges, and implications of integrating AI tools and techniques into library cataloging practices. Chapter 1 provides an introduction to the research topic, outlining the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definitions of key terms. The chapter sets the stage for understanding the importance of leveraging AI in library cataloging and metadata management. Chapter 2 consists of a comprehensive literature review that examines existing research and studies related to AI applications in library and information science. The review covers topics such as machine learning, natural language processing, semantic web technologies, and automation in library cataloging processes. By analyzing previous works, this chapter establishes a theoretical framework for the study. Chapter 3 details the research methodology employed in this study, including the research design, data collection methods, data analysis techniques, and ethical considerations. The chapter also describes the selection criteria for AI tools and models used in the research and provides a rationale for the chosen approach. Chapter 4 presents the findings of the study, highlighting the outcomes of implementing AI technologies in library cataloging and metadata management. The chapter discusses the performance of AI algorithms in enhancing the accuracy and efficiency of cataloging processes, as well as the impact on metadata quality and discoverability of library resources. Chapter 5 offers a conclusion and summary of the thesis, drawing insights from the research findings and discussing implications for practice and future research directions. The chapter also reflects on the potential challenges and ethical considerations associated with the adoption of AI in libraries, emphasizing the need for continuous evaluation and improvement of AI-driven cataloging systems. In conclusion, this thesis contributes to the growing body of knowledge on the application of AI in library and information science, specifically focusing on its role in enhancing library cataloging and metadata management. By exploring the opportunities and challenges of integrating AI technologies into library workflows, this study provides valuable insights for librarians, information professionals, and researchers seeking to leverage AI for improving library services and resource discovery.