Abstract
This study is dedicated to evaluating the effectiveness of online platforms in the educational application of adolescent mental health. Using clustering algorithms, C4.5 decision trees, and item-based collaborative filtering techniques, this paper explores strategies for constructing mental health portraits and recommending educational videos. The results show that these techniques enable online platforms to accurately identify students’ mental states and provide customized educational content. In a three-month experiment, the platform effectively enhanced the psychological state of adolescents through mental health education. After use, students’ self-assessed mental health increased by 15\% and showed significant improvement in coping with stress and adapting to new environments. The study shows that the online education platform has a significant facilitating role in the field of adolescent mental health education and can provide effective mental health support for adolescents.
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