Thesis Abstract

Abstract
This thesis investigates the utilization of artificial intelligence (AI) to enhance information retrieval systems within library settings. The advent of AI technologies has revolutionized various industries, and this research aims to explore how AI can be leveraged to improve the efficiency and effectiveness of information retrieval processes in libraries. The study is motivated by the growing need for libraries to keep pace with technological advancements and provide users with seamless access to information resources. The research begins with a comprehensive review of the background of the study, highlighting the evolution of information retrieval systems in libraries and the challenges faced in the current landscape. The problem statement identifies the limitations of traditional systems and the potential benefits that AI can offer in terms of enhancing search capabilities, personalizing user experiences, and optimizing information organization and retrieval. The objectives of the study are outlined to investigate the impact of AI on information retrieval systems, assess the feasibility of implementing AI technologies in libraries, and evaluate the user perception and acceptance of AI-powered systems. The limitations of the study are acknowledged, including constraints related to resources, time, and access to data. The scope of the study is defined to focus on specific AI applications such as natural language processing, machine learning, and recommendation systems within the context of library information retrieval. The significance of the study lies in its potential to contribute to the advancement of library services by harnessing AI technologies to improve the overall user experience and information access. The structure of the thesis is outlined to provide a roadmap of the research methodology, literature review, discussion of findings, and conclusion. The literature review delves into existing research and developments in the application of AI in library settings, highlighting key studies, methodologies, and outcomes. The research methodology section details the approach, data collection methods, data analysis techniques, and ethical considerations employed in the study. It includes a description of the research design, sampling strategy, data collection instruments, and data analysis procedures. The discussion of findings presents the results of the research, including insights into the impact of AI on information retrieval systems, user perceptions, and challenges encountered during implementation. The chapter explores the implications of the findings for library practitioners, policymakers, and researchers, offering recommendations for future research and practical applications. In conclusion, this thesis provides a comprehensive analysis of the role of AI in enhancing information retrieval systems in libraries, emphasizing the potential benefits, challenges, and implications of integrating AI technologies into library services. The study contributes to the body of knowledge on AI applications in library and information science, offering insights into the future of information retrieval systems and the evolving role of libraries in the digital age.

Thesis Overview