Article: An ELM-based approach to promoting reading of library books Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.2 pp.82 - 95 Abstract: Personalised book recommendations have become a major difficulty given the fast growth of digital resources and online libraries. This work presents a hybrid recommender system based on extreme learning machine (ELM) to improve the accuracy and diversity of book recommendations in libraries. Combining content-based filtering and collaborative filtering, the system uses the advantages of both techniques above their respective restrictions. The suggested system effectively handles extensive user behaviour and book information by including ELM, which provides fast training and high generalising capacity. Comparatively to conventional approaches, experimental data reveal that the hybrid model considerably increases suggestion accuracy, diversity, and coverage. Key parameters used in evaluation of the system include precision, recall, variety, and coverage, therefore proving its possible use in library book recommendation systems. Inderscience Publishers - linking academia, business and industry through research

Title: An ELM-based approach to promoting reading of library books

Authors: Tianhao Wu

Addresses: Library, Changchun University of Technology, Changchun 130000, China

Abstract: Personalised book recommendations have become a major difficulty given the fast growth of digital resources and online libraries. This work presents a hybrid recommender system based on extreme learning machine (ELM) to improve the accuracy and diversity of book recommendations in libraries. Combining content-based filtering and collaborative filtering, the system uses the advantages of both techniques above their respective restrictions. The suggested system effectively handles extensive user behaviour and book information by including ELM, which provides fast training and high generalising capacity. Comparatively to conventional approaches, experimental data reveal that the hybrid model considerably increases suggestion accuracy, diversity, and coverage. Key parameters used in evaluation of the system include precision, recall, variety, and coverage, therefore proving its possible use in library book recommendation systems.

Keywords: extreme learning machine; ELM; hybrid recommender system; library books; personalised book recommendations.

DOI: 10.1504/IJICT.2025.144057

International Journal of Information and Communication Technology, 2025 Vol.26 No.2, pp.82 - 95

Received: 08 Dec 2024
Accepted: 18 Dec 2024
Published online: 22 Jan 2025 *

Title: An ELM-based approach to promoting reading of library books

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