From traditional to tech-savvy: the evolution of Nigerian libraries in the machine learning era

Author:

Adewojo Akinade Adebowale,Akanbiemu Adetola Adebisi,Onuoha Uloma Doris

Abstract

Purpose This study explores the implementation of personalised information access, driven by machine learning, in Nigerian public libraries. The purpose of this paper is to address existing challenges, enhance the user experience and bridge the digital divide by leveraging advanced technologies. Design/methodology/approach This study assesses the current state of Nigerian public libraries, emphasising challenges such as underfunding and lack of technology adoption. It proposes the integration of machine learning to provide personalised recommendations, predictive analytics for collection development and improved information retrieval processes. Findings The findings underscore the transformative potential of machine learning in Nigerian public libraries, offering tailored services, optimising resource allocation and fostering inclusivity. Challenges, including financial constraints and ethical considerations, are acknowledged. Originality/value This study contributes to the literature by outlining strategies for responsible implementation and emphasising transparency, user consent and diversity. The research highlights future directions, anticipating advancements in recommendation systems and collaborative efforts for impactful solutions.

Publisher

Emerald

Reference37 articles.

1. Fostering comfort and inclusivity in library environments: exploring factors influencing the avoidance of reading within the library;Journal of Access Services,2023

2. Multicriteria decision making taxonomy of code recommendation system challenges: a fuzzy-AHP analysis;Information Technology and Management,2023

3. Management of academic library services in the 21st century digital dispensation;Alexandria,2023

4. Foregrounding women’s safety in mobile social matching and dating apps: a participatory design study;Proceedings of the ACM on Human-Computer Interaction,2023

5. The applications of machine learning techniques in medical data processing based on distributed computing and the internet of things;Computer Methods and Programs in Biomedicine,2023

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