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Music teaching in universities is very important for students majoring in music. The quality of its teaching will directly affect students’ professional abilities and even affect their future employment (Jackson & Liggett, 2020). Music is a very important art subject, which has a significant influence on the cultivation of students’ artistic and moral concepts. Therefore, music teaching has become an important topic in tertiary education (Mai et al., 2022). In recent years, universities have set up music elective courses for non-music majors and also created a group of high-quality music teachers, which has contributed to the growth of music teaching (Costa et al., 2017). Music reform in universities can effectively improve the instructional level, combine new science and technology, promote the growth of the music discipline, and make the music discipline itself change positively. At the same time, it can optimize teaching methods, enhance students’ initiative in learning, and strengthen the effectiveness of music teaching (Meng, 2019). With the further popularization of internet technology, people can swim in the ocean of information anytime and anywhere. The quantity of information is no longer a problem, and how to obtain effective information conveniently and quickly, and even get individuation information service, has increasingly become the focus of research in all walks of life (He et al., 2021).
The establishment of a music major is conducive to improving the standard of campus culture in universities, improving the standard of running schools and education, and cultivating popular music talents (Xiaofeng, 2021). With the surge of information on the internet, information search technology is facing more and more challenges (Schlaseman, 2019). It is difficult for traditional search engines to meet the individuation needs of users, and it is increasingly difficult for people to find the resources they need accurately and quickly. To address this problem, so recommendation technology came into being. As an integral part of educational informatization, instructional resources reflect important significance in teaching (Ruiz et al., 2021). The online instructional platform contains a large quantity of instructional resources, but it usually provides users with the same resources (Yuan, 2021). Because users have different interests and hobbies, the demand for instructional resources is also different (Gong et al., 2018).
Traditional social recommendation systems cannot improve user satisfaction without clear requirements (Sato & Chen, 2021). Personalized recommendation technology can solve information overload. By uploading a series of actions to a user, it creates a separate model for each user and recommends the user’s preferred content (Yancey, 2019). For example, the “recommended song list” of various music platforms uses this technology to mine and recommend songs that customers like, which saves users time. Aiming at the sparsity of traditional recommendation algorithms, an improved collaborative filtering (CF) algorithm is designed. In this paper, the authors combine the actual situation and mine the large amount of data generated in online music education to obtain useful information and realize personalized recommendations for music teaching resources in colleges and universities. For the sparsity of the traditional recommendation algorithm, an improved CF algorithm is designed to improve the recommendation quality by focusing on the processing of noise points while ensuring the recommendation efficiency. It provides references for the reform of contemporary music discipline growth.