Project Abstract

Abstract
This research project focuses on the implementation of Artificial Intelligence (AI) for developing personalized recommendation systems in libraries. The aim of this study is to enhance user experience and improve the efficiency of information retrieval for library patrons. The integration of AI technology into library systems allows for the customization of recommendations based on user preferences, browsing history, and behavior patterns. By leveraging AI algorithms, libraries can provide tailored suggestions for books, articles, and other resources, thereby facilitating a more engaging and personalized experience for users. The research begins with an introduction that outlines the background of the study, identifies the problem statement, and sets forth the objectives of the research. The limitations and scope of the study are also defined, along with an explanation of the significance of implementing AI-powered recommendation systems in libraries. The structure of the research is detailed, providing a roadmap for the subsequent chapters. Chapter two presents a comprehensive literature review that examines existing studies and frameworks related to AI-based recommendation systems in libraries. The review encompasses ten key areas, including AI technologies, recommendation algorithms, user modeling, and evaluation metrics. By synthesizing prior research, this chapter lays the foundation for understanding the current state of personalized recommendation systems in library settings. Chapter three delves into the research methodology employed in this study, covering eight essential components such as research design, data collection methods, AI model selection, and evaluation criteria. The methodology section outlines the steps taken to develop and implement the AI-driven recommendation system, ensuring transparency and reproducibility in the research process. In chapter four, the discussion of findings provides a detailed analysis of the results obtained from the implementation of the personalized recommendation system in a library environment. Seven key findings are discussed, highlighting the effectiveness of AI algorithms in generating relevant and personalized recommendations for users. The chapter also addresses potential challenges, limitations, and areas for future research and improvement. Finally, chapter five offers a conclusion and summary of the research project, encapsulating the key findings, implications, and contributions to the field of library and information science. The conclusion reflects on the significance of utilizing AI for personalized recommendation systems in libraries and offers recommendations for further research and practical applications. Overall, this research project demonstrates the potential of AI technology to revolutionize library services by providing tailored recommendations that enhance user engagement and satisfaction. By leveraging AI capabilities, libraries can adapt to the evolving needs and preferences of their patrons, ultimately improving the accessibility and usability of information resources within a digital age context.

Project Overview