Evolving Impact of Artificial Intelligence on Bibliomining and Scholarly Knowledge Systems

Artificial intelligence is transforming bibliomining, the systematic study of scholarly literature, by introducing advanced technological approaches. This evolution is evident across three key areas: 1) Machine learning enhances pattern recognition in authors, publications, and research topics, thereby improving recommendation systems and library services. 2) Natural language processing (NLP) facilitates semiotic analysis of library catalogues, enabling effective topic analysis and comprehension of user preferences. 3) Deep learning is employed for predictive modelling, forecasting research trends, user behaviour, and information needs. These advancements collectively improve information retrieval, metadata creation, customised searches, and data-assisted decision-making, contributing to the development of new library resources and proactive services powered by expert systems. This study provides an outlook on AI's future role in academic libraries and information provision.