Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2024)

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Exploiting the Spectrum of Perturbed Even-Order Operators in Optimizing Educational Recommendation Systems (OERS)

Authors
Ilias Aarab1, *, Youssef Jdidou2, Souhaib Aammou3
1Abdelmalek Essaadi University, Tetuan, Morocco
2Ecole Marocaine des Sciences de l‘Ingénieur, Laboratory of Intelligent Systems and Applications (LSIA), Tangier, Morocco
3S2IPU, ENS, Abdelmalek Essaadi University, Tetuan, Morocco
*Corresponding author. Email: ilias.aarab1989@gmail.com
Corresponding Author
Ilias Aarab
Available Online 20 June 2025.
DOI
10.2991/978-2-38476-408-2_3How to use a DOI?
Keywords
Educational Recommendation Systems (ERS); Optimization of Recommendation Algorithms; Spectrum of Perturbed Even-Order Operators; Personalization of Learning; Computational Efficiency
Abstract

In the field of online education, personalization of learning is a major challenge. Educational recommendation systems (ERS) play a crucial role in proposing resources tailored to the individual needs of learners. This article explores an innovative approach to optimize ERS by exploiting the spectrum of perturbed even-order operators. We demonstrate how theoretical results associated with these operators can improve the accuracy and efficiency of recommendation algorithms, especially in the context of large data dimensions and detection of complex learning patterns. We propose an optimized recommendation model and evaluate its performance on a simulated educational dataset. The results show a significant improvement in precision, recall, and F1 score compared to conventional approaches, while reducing computation time.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2024)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
20 June 2025
ISBN
978-2-38476-408-2
ISSN
2667-128X
DOI
10.2991/978-2-38476-408-2_3How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ilias Aarab
AU  - Youssef Jdidou
AU  - Souhaib Aammou
PY  - 2025
DA  - 2025/06/20
TI  - Exploiting the Spectrum of Perturbed Even-Order Operators in Optimizing Educational Recommendation Systems (OERS)
BT  - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2024)
PB  - Atlantis Press
SP  - 20
EP  - 31
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-2-38476-408-2_3
DO  - 10.2991/978-2-38476-408-2_3
ID  - Aarab2025
ER  -