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.

Thesis Overview

The project titled "Utilizing Artificial Intelligence for Enhancing Library Cataloging and Metadata Management" aims to explore the potential applications of artificial intelligence (AI) in the field of library science. In recent years, the exponential growth of digital information has posed significant challenges to traditional library cataloging and metadata management processes. The sheer volume and diversity of resources available online require more efficient and effective methods for organizing, classifying, and retrieving information. The research will delve into the current landscape of library cataloging and metadata management practices, highlighting the limitations and inefficiencies that exist in manual processes. By leveraging AI technologies such as machine learning, natural language processing, and computer vision, this study seeks to develop innovative solutions to enhance the accuracy, speed, and scalability of library cataloging and metadata management. Through a comprehensive literature review, the project will examine existing research and case studies that have explored the integration of AI in library and information science. By identifying best practices and emerging trends in the field, the research aims to build upon existing knowledge and contribute new insights to the discourse on AI applications in libraries. The methodology section of the project will outline the research design, data collection methods, and analytical techniques that will be employed to investigate the research questions. By combining qualitative and quantitative approaches, the study will gather empirical evidence to evaluate the effectiveness of AI-based solutions in improving library cataloging and metadata management processes. The findings of the research will be presented in the discussion chapter, where the implications of the results will be interpreted in the context of existing theories and practical implications. By critically analyzing the outcomes of the study, the project aims to provide actionable recommendations for libraries seeking to adopt AI technologies to enhance their information management practices. In conclusion, the project on "Utilizing Artificial Intelligence for Enhancing Library Cataloging and Metadata Management" seeks to advance the field of library and information science by exploring the transformative potential of AI in addressing the challenges of information organization and retrieval. By harnessing the power of AI, libraries can streamline their cataloging processes, improve metadata quality, and enhance user access to information resources in the digital age.