Thesis Abstract

Abstract
This thesis focuses on the utilization of Artificial Intelligence (AI) for enhanced metadata management in digital libraries. The rapid growth of digital content in libraries necessitates efficient organization and retrieval methods, which can be facilitated through AI technologies. The study aims to investigate how AI can be implemented to improve metadata management processes, leading to more effective information organization and retrieval within digital library systems. The research begins with an exploration of the current state of metadata management in digital libraries and the challenges faced in organizing and retrieving information efficiently. By examining existing literature on AI applications in information science and digital libraries, the study establishes a foundation for the potential benefits of integrating AI into metadata management systems. The methodology chapter outlines the research approach, including data collection methods, analysis techniques, and the implementation of AI algorithms for metadata management. The study employs a combination of qualitative and quantitative research methods to examine the effectiveness of AI tools in enhancing metadata organization and retrieval processes. The findings chapter presents the results of the research, highlighting the impact of AI on metadata management in digital libraries. Through empirical analysis and case studies, the study demonstrates the efficacy of AI technologies in improving metadata accuracy, relevance, and search capabilities. The discussion chapter delves into the implications of these findings, discussing the practical applications of AI in optimizing metadata management practices within digital library environments. In conclusion, this thesis emphasizes the significance of leveraging AI for improved metadata management in digital libraries. By harnessing the power of AI algorithms, libraries can enhance information organization, retrieval efficiency, and user experience. The study contributes to the advancement of digital library practices by demonstrating the benefits of integrating AI technologies into metadata management systems. Overall, this research underscores the potential of AI to revolutionize metadata management processes and transform the way digital libraries operate in the modern information landscape.

Thesis Overview

The project titled "Utilizing Artificial Intelligence for Improved Metadata Management in Digital Libraries" aims to explore the potential of artificial intelligence (AI) in enhancing metadata management within digital libraries. In recent years, digital libraries have become crucial resources for accessing and managing vast amounts of digital information. However, the efficiency and effectiveness of digital libraries heavily rely on the quality and organization of metadata associated with digital resources. The research will delve into how AI technologies, such as machine learning algorithms and natural language processing, can be leveraged to automate and improve metadata creation, enrichment, and maintenance processes in digital libraries. By harnessing the power of AI, the project seeks to address issues related to metadata quality, consistency, and scalability, ultimately enhancing the overall user experience and information retrieval capabilities of digital library systems. Through a comprehensive literature review, the project will explore existing studies, methodologies, and best practices related to AI applications in metadata management and digital libraries. This review will provide a solid foundation for understanding the current state-of-the-art technologies and approaches in the field and identify gaps and opportunities for further research. The research methodology will involve the development and implementation of AI-based tools and algorithms tailored to the specific needs and challenges of metadata management in digital libraries. Data collection, experimentation, and evaluation processes will be conducted to assess the performance and effectiveness of the proposed AI solutions in improving metadata quality, accuracy, and relevance. The findings of the study will be presented and discussed in detail, highlighting the impact of AI technologies on metadata management processes and the overall performance of digital library systems. Insights gained from the research will not only contribute to the academic discourse on AI applications in information science but also offer practical recommendations for digital library practitioners and developers seeking to optimize metadata workflows and enhance user satisfaction. In conclusion, the project "Utilizing Artificial Intelligence for Improved Metadata Management in Digital Libraries" represents a significant contribution to the field of library and information science by exploring innovative ways to harness AI for enhancing metadata management practices in digital environments. The research outcomes are expected to advance the capabilities of digital libraries, improve information access and retrieval, and pave the way for future advancements in AI-driven library technologies.