Accurate Recommendation of Personalized Mobile Teaching Resources for Piano Playing and Singing Based on Collaborative Filtering Algorithm

With the rapid development of education informatization, online education resources are growing explosively. In order to avoid the waste of resources and enable piano playing and singing learners to accurately and quickly find the mobile teaching resources courses they are interested in the massive resources, this paper proposes a precise recommendation method of personalized piano playing and singing mobile teaching resources based on collaborative filtering algorithm. Through the context awareness method, we can obtain the demand information of learners in real time, store it in the database, and calculate the degree of interest of piano playing and singing learners on this basis. Based on the collaborative filtering algorithm, we can constantly optimize the accuracy of the algorithm through the analysis of the degree of interest of learners and other information, accurately recommend learning resources for piano playing and singing, and improve the learning effect and interests of learners. The experimental results show that the proposed method has achieved good application results in practice, and has certain reference and guidance value for enhancing the learning interest of piano playing and singing learners and cultivating autonomous learning ability.