The Application of Artificial Intelligence and Machine Learning in Academic Libraries

Abstract

The study was based on a review of 61 articles selected from 127 journal articles from Springer, Elsevier, Routledge, Sage, EmeraldInsight, Jstir, ATLANTIS, IFLA, and DigitalCommons. The study showed that artificial intelligence and machine learning have been used in libraries to support reference services, indexing and abstracting, information retrieval, cataloguing and classification, and collection management, among other services. Machine learning techniques such as the KNearest neighbour, Bayesian networks, fuzzy logic, support vector machines, clustering, and classification algorithms were also used. Key challenges that hindered the adoption of artificial intelligence and machine learning among libraries included a lack of infrastructure, lack of funding, and lack of awareness among librarians. The study recommended training of librarians and curriculum reviews for library schools. It also recommended further research on Python-based innovations for libraries.