Download pdf
Book Recommendation System
- 1 NO.1 Middle School Affiliated to Central China Normal University, Wuhan, 430079, China
- 2 Sanjiang University, Nanjing, 210012, China
- 3 Hertfordshire, Hatfield, AL10 9BL, United Kingdom
* Author to whom correspondence should be addressed.
Abstract
This study presents a personalized book recommendation system designed to assist students in selecting appropriate study materials based on their grade levels and subject preferences. Unlike general AI models such as ChatGPT, our system tailors book recommendations by integrating user feedback and leveraging targeted personalization. The development process consisted of multiple iterations involving user-centered design and evaluation, including surveys, low-fidelity prototype testing, and high-fidelity prototype evaluation. Findings show that the system effectively meets the unique needs of students by providing accessible, relevant, and customized recommendations. The results indicate that our personalized approach improves user satisfaction and addresses challenges that traditional book recommendation systems face, such as lack of relevance and complexity in navigation.
Keywords
book recommendation, large language model, general recommendation, ChatGPT
[1]. Wu, S., Huang, Y. and Zhao, C., 2023. ChatGPT for Conversational Recommendation: Refining Recommendations by Reprompting with Feedback. arXiv preprint. Available at: https://arxiv.org/abs/2401.03605.
[2]. Di Palma, D., Santoro, M., Sordoni, A., and Marcolin, G., 2023. Evaluating ChatGPT as a Recommender System: A Rigorous Approach. arXiv preprint. Available at: https://arxiv.org/abs/2309.03613.
[3]. Zhang, Y., Li, Z. and Chen, L., 2023. Uncovering ChatGPT’s Capabilities in Recommender Systems. arXiv preprint. Available at: https://arxiv.org/abs/2305.02182.
[4]. Gao, Y., Lim, C. and Wang, Z., 2023. Is ChatGPT a Good Recommender? A Preliminary Study. arXiv preprint. Available at: https://arxiv.org/abs/2304.10149.
[5]. Rahman, M.S., and Zaman, M., 2023. ChatGPT and Academic Research: A Review and Recommendations. ResearchGate. Available at: https://www.researchgate.net/publication/370096679_ChatGPT_and_Academic_Research_A_Review_and_Recommendations.
[6]. Gabashvili, I.S., 2023. The Impact and Applications of ChatGPT: A Systematic Review of Literature Reviews. arXiv preprint. Available at: https://arxiv.org/abs/2305.18086.
[7]. Montenegro-Rueda, M. and Fernández-Cerero, J., 2023. Impact of the Implementation of ChatGPT in Education: A Systematic Review. Computers, 12(8), pp.153. Available at: https://doi.org/10.3390/computers12080153.
Cite this article
Yu,Z.;Zhan,Y.;Liu,D. (2025). Book Recommendation System. Applied and Computational Engineering,131,132-140.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).