Design and Research of Studentsâ€™ Secured Education System Based on Personalized Recommendation
Hao Qin
Journal of Information Security Research, Vol. 16, No. 1, 2025.
DOI: https://doi.org/10.6025/jisr/2025/16/1/25-32
Link: https://www.dline.info/jisr/fulltext/v16n1/jisrv16n1_4.pdf
Abstract:
This study aims to develop a secure education solution that meets the individual needs of different college
students, helping them grasp knowledge better, enhance their learning enthusiasm, and stimulate their motivation.
The research adopts experimental design and analysis methods, setting up experimental and control
groups, collecting experimental data, and conducting data analysis. The matrix factorization algorithm is
used to obtain a suitable system, and the experimental results show that personalized recommendation systems
can recommend secure education resources that meet the usersâ€™ needs based on their personal characteristics
and interests, thereby increasing their attention and interest in learning and enhancing learning effectiveness.
The college studentsâ€™ secure education system based on personalized recommendation has potential
and room for development, and its performance and user experience can be improved through continuous
optimization of recommendation strategies and algorithms. This research provides valuable references for
the design and study of personalized recommendation systems in college studentsâ€™ secure education.