Implementation of Artificial Intelligence in Library Cataloging and Classification

Thesis Abstract

Abstract
The integration of Artificial Intelligence (AI) in library cataloging and classification has the potential to revolutionize information organization and retrieval processes. This thesis explores the implementation of AI technologies in improving the efficiency and effectiveness of library cataloging and classification systems. The research investigates how AI algorithms can enhance the accuracy and speed of metadata creation, classification, and indexing of library resources. The study begins with an introduction to the significance of AI in the field of Library and Information Science, highlighting the growing importance of technology in managing and accessing vast amounts of information. The background of the study provides an overview of traditional library cataloging methods and the challenges associated with manual classification processes. The problem statement identifies the limitations of current cataloging systems in meeting the evolving information needs of users and highlights the potential benefits of incorporating AI technologies. The objectives of the study focus on evaluating the impact of AI on library cataloging efficiency, accuracy, and user satisfaction. The research methodology chapter outlines the approach taken to investigate the implementation of AI in library cataloging and classification. It includes details on data collection methods, AI algorithm selection, and evaluation criteria for measuring the performance of AI-enhanced cataloging systems. The literature review section explores existing studies and projects that have implemented AI in library settings. It discusses the various AI techniques used for automated metadata creation, subject classification, and indexing. The chapter also examines the challenges and opportunities associated with AI adoption in library cataloging processes. The findings chapter presents a detailed analysis of the results obtained from implementing AI in library cataloging and classification. It evaluates the impact of AI on metadata accuracy, classification consistency, and user satisfaction. The discussion delves into the implications of these findings for library professionals, users, and information retrieval practices. The conclusion and summary chapter consolidate the key findings of the study and provide recommendations for future research and implementation of AI in library cataloging and classification. It emphasizes the potential of AI technologies to enhance information organization and access in libraries, paving the way for more efficient and user-centric services. In conclusion, this thesis contributes to the growing body of research on the application of AI in Library and Information Science. By exploring the implementation of AI in library cataloging and classification, this study offers insights into the benefits and challenges of integrating AI technologies into traditional library practices.