Development and Integration Model of Online Music Education Resources Based on Collaborative filtering Algorithm

With the continuous popularization and development of network technology in recent years, the growth of information on the Internet presents an explosive speed. Such huge information brings retrieval difficulties to users, and the traditional search engine technology is difficult to meet the needs of users. Under the background that the existing technology can not meet the needs, Collaborative filtering algorithm(CFA) system has emerged, and then developed into a research hotspot of recommendation leading city. With the development of science and technology, online music appears in everyone’s vision. In order to improve the existing management mode of music resources, we should integrate and develop online music resources according to the characteristics of educational resources. In order to make efficient use of music resources, it is necessary to change the traditional management mode of music resources. The common ways are: designing a more efficient and fast way to search music resources; Upgrade the original music database; Improve the existing management mode of music database. In this paper, by importing weighting factors, the project-based filtering and user based filtering are integrated to build a new intelligent filtering algorithm for music recommendation, and the performance of the recommendation algorithm is verified by key indicators. The conclusion shows that this method can provide users with high accuracy music education.