Utilizing Artificial Intelligence for Personalized Recommendation Systems in Libraries

Thesis Abstract

Abstract
The advancement of technology has revolutionized the way information is accessed and utilized in various fields, including libraries. This thesis explores the implementation of Artificial Intelligence (AI) in the development of personalized recommendation systems in libraries. The aim of this study is to investigate how AI technologies can be leveraged to enhance user experience and provide tailored recommendations to library patrons based on their preferences and behavior. Chapter One provides an introduction to the research topic, presenting the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. The chapter sets the foundation for understanding the application of AI in library settings. Chapter Two consists of a comprehensive literature review that explores existing studies, theories, and models related to AI, recommendation systems, and library technology. The review highlights the importance of personalized recommendations in enhancing user engagement and satisfaction in libraries. Chapter Three outlines the research methodology employed in this study, including research design, data collection methods, sample selection, data analysis techniques, and ethical considerations. The chapter provides a detailed overview of the steps taken to conduct the research and collect relevant data. Chapter Four presents the findings of the study, analyzing the implementation of AI-based recommendation systems in libraries and their impact on user experience. The chapter discusses the effectiveness of personalized recommendations in improving access to information and engaging library users. Finally, Chapter Five offers a conclusion and summary of the thesis, highlighting the key findings, implications, and recommendations for future research. The study concludes that AI technologies hold great potential for transforming library services through personalized recommendation systems, ultimately enhancing user satisfaction and promoting information access. In conclusion, this thesis contributes to the growing body of knowledge on the integration of AI in library services and the development of personalized recommendation systems. By leveraging AI technologies, libraries can enhance user experience, promote information discovery, and adapt to the evolving needs of patrons in the digital age.