- 年份:2023 年
- 編號:344
- Topic分類:11
- Topic分數:0.4183682777
- Publish:2023 International Conference on Disruptive Technologies (ICDT)
- 作者:Sapna Bisht; Ajay Prasad Nautiyal; Setu Sharma; Manish Sati; Neha Bathla; Pardeep Singh
Keywords:AI, Library, Utilization, Technology, Management, cataloging
Abstract:The role of Artificial Intelligence in shaping Library Management and its Utilization Artificial IntelligenceAIhas been increasingly shaping the library management landscape in recent yearsThe integration of AI technology has the potential to greatly enhance the efficiencyaccuracyand user experience in library catalogingmanagementand operationsThis paper aims to explore the role of AI in shaping library management and its utilizationThe increasing utilization of AI in libraries is driven by advances in technology and increased awareness of the potential benefitssuch as improved accuracy and efficiency in library data managementenhanced user experienceand cost savingsThe paper will also provide a rough timeline of the increasing utilization of AI in library management and operations over the past few yearsFinallythe paper will discuss the limitations and challenges of AI adoption in librariesand outline some of the key considerations for libraries looking to integrate AI into their operationsThe findings of this research will provide valuable insights into the role of AI in shaping library management and its utilizationand help libraries make informed decisions about technology investments and operationsLibrary AutomationAI can automate classificationcirculation and reference services to improve efficiencyCollection ClassificationUse NLP and machine learning to automatically classifyRetrieval and IndexingAI can enhance search and index functionsand it is easier for users to find the required informationUse NLP and machine learning algorithms to analyze and classify a large amount of data to achieve faster and more accurate classificationsThe AI-driven reference system uses NLP and machine learning algorithms for data analysisIt is easier for users to find the required informationAI-driven recommendation system uses data analysis to provide users with personalized recommendations to help them find the required information more quickly and easier
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