In an era marked by rapid technological progress, libraries find themselves at a crossroads grappling with the challenges posed by an information-rich yet digitally fragmented landscape. The conventional role of libraries, once the steadfast guardians of knowledge, faces disruption as we navigate through a sea of information abundance. This conundrum gives rise to a critical issue - how can libraries adapt and thrive in an environment dominated by the rapid evolution of artificial intelligence (AI)? AI-Assisted Library Reconstruction is a compelling solution that promises to breathe new life into these institutions, making them more dynamic, accessible, and efficient in the face of unprecedented challenges. This book addresses the pressing issues faced by libraries in the age of information technology. It doesn't merely scratch the surface; it delves deep into the heart of the matter, providing an exploration of the integration of artificial intelligence in the reconstruction and revitalization of libraries. Through an in-depth examination of technologies, methodologies, and applications, it offers a guide for libraries to not only survive but thrive in this technologically charged landscape. Designed with academic scholars, librarians, and information professionals in mind, this book aims to resonate with those seeking a nuanced understanding of the challenges posed by AI integration in library services. Beyond the academic realm, it speaks to technologists, administrators, policymakers, and even the broader audience interested in the delicate dance between traditional library values and the dynamic advancements brought about by AI. As libraries stand at the brink of technological transformation, AI-Assisted Library Reconstruction paves the way for a future where traditional values harmonize seamlessly with the dynamic innovations brought forth by AI.
K. R. Senthilkumar works as a Librarian in Sri Krishna Arts and Science College, Coimbatore. His most notable contributions to the field of E- Library and the Development of Library Web page. His research interests span both bibliometrics and Web 2.0. Much of his work has been on improving the understanding, design, and performance of Information systems, mainly through the application of E- Library, Survey, and Compare evaluation. In the Information Science arena, he has worked on TN Public Online Library. He has explored the presence and implications of self-similarity and heavy-tailed distributions in Open Source Journals. He has also investigated the implications of Web workloads for the design of scalable and no cost-effective Web Pages. In addition, he has made numerous contributions to research papers like Journals, Conference and Book Chapters
