Thesis Abstract

Abstract
The rapid advancements in technology have significantly impacted various sectors, including libraries and information science. This thesis focuses on the implementation of Artificial Intelligence (AI) in library cataloging and classification systems. The integration of AI technologies in library operations has the potential to revolutionize traditional practices, enhance efficiency, and improve user experience. Chapter 1 provides an introduction to the research topic, discussing the background of the study, the problem statement, objectives, limitations, scope, significance, structure of the thesis, and definitions of key terms. The aim is to set the stage for the exploration of AI in library cataloging and classification systems. Chapter 2 delves into a comprehensive literature review, examining existing studies, frameworks, and applications related to AI in library settings. The review covers various aspects such as AI technologies, machine learning algorithms, natural language processing, and their relevance to library cataloging and classification. Chapter 3 outlines the research methodology employed in this study. It includes detailed descriptions of research design, data collection methods, sampling techniques, data analysis procedures, and ethical considerations. The chapter aims to provide transparency regarding the research process adopted for this investigation. Chapter 4 presents the findings of the study, highlighting the outcomes of implementing AI in library cataloging and classification systems. The discussion explores the advantages, challenges, and implications of AI integration, drawing insights from data analysis, case studies, and user feedback. Chapter 5 concludes the thesis by summarizing the key findings, discussing the implications for practice and future research directions. The conclusion reflects on the potential of AI to transform library services, improve information retrieval processes, and enhance user engagement. Overall, this thesis contributes to the growing body of knowledge on AI applications in library and information science, paving the way for innovative practices in cataloging and classification systems.

Thesis Overview

Research Overview: The project titled "Implementation of Artificial Intelligence in Library Cataloging and Classification Systems" aims to explore the integration of artificial intelligence (AI) technologies into traditional library cataloging and classification processes. Libraries play a crucial role in information organization and retrieval, and the adoption of AI has the potential to revolutionize these fundamental functions. By leveraging AI algorithms and machine learning techniques, libraries can enhance the efficiency, accuracy, and relevance of cataloging and classification systems, ultimately improving user access to information resources. The research will begin with an in-depth investigation into the background of library cataloging and classification practices, highlighting the challenges and limitations faced by traditional systems in the digital age. The project will then define the problem statement, outlining the inefficiencies and constraints that current cataloging and classification methods pose for libraries and their users. The objectives of the study include assessing the feasibility and benefits of implementing AI in library cataloging and classification, developing AI-based models for automated metadata generation and resource categorization, and evaluating the impact of AI technologies on information retrieval and user experience in libraries. The research methodology will involve a comprehensive literature review to explore existing AI applications in libraries, identify best practices and case studies, and analyze the implications of AI adoption for information professionals. The study will also involve data collection through surveys, interviews, and experiments to gather insights from librarians, technologists, and library users regarding their perceptions and expectations of AI-enhanced cataloging and classification systems. The findings of the research will be presented in a detailed discussion, highlighting the opportunities, challenges, and implications of integrating AI into library workflows. The analysis will cover aspects such as system performance, data quality, user acceptance, ethical considerations, and the potential for collaboration between AI systems and human catalogers. In conclusion, the project will provide a comprehensive summary of the research outcomes, emphasizing the significance of AI in transforming library cataloging and classification practices. The study aims to contribute to the advancement of information science by showcasing the potential of AI technologies to enhance resource discovery, knowledge organization, and information access in libraries, thereby paving the way for a more efficient and user-centric library ecosystem.