In the field of preschool education, effective sharing and recommendation of educational resources are crucial for promoting the best learning environment. This chapter explores the application of collaborative filtering algorithms in preschool education resource sharing platforms. Traditional recommendation systems often face challenges in scalability and accuracy of diverse educational environments. This chapter aims to address these issues by implementing a hybrid collaborative filtering method that combines users and projects. Through comprehensive experiments, it has been proven that the method proposed in this chapter is significantly superior to traditional methods in terms of recommendation accuracy and efficiency. We also evaluated user satisfaction through surveys and analyzed the impact on student learning outcomes, highlighting the practical benefits of the system. In addition, scalability and computational efficiency were evaluated to ensure the feasibility of large-scale deployment of the system. This study provides valuable insights into integrating advanced recommendation algorithms into educational platforms, paving the way for more personalized and effective learning experiences.