Personalized Services Based on Big Data Algorithms—taking Netease Cloud as an Example

Abstract

Based on the rapid development of network technology and the arrival of the digital era, big data algorithms have gradually penetrated various fields, providing great convenience for users. The research focus of this paper is to analyze deeply how big data algorithms are widely used in personalized services. It will also take the music service platform NetEase Cloud as an example to explore its effects on improving user satisfaction, customized services, and optimization of recommendation systems. By analyzing the specific practices of NetEase Cloud, this article reveals the application value of big data algorithms in building user profiles, providing personalized services, optimizing recommendation systems, and providing competitive advantages in the music industry. In addition, the platform accurately meets user needs. It optimizes intelligent recommendations dynamically by integrating users' historical behavioral data and user feedback, improving NetEase Cloud's competitive advantage in music platforms. The significance of this research is to explore the strong competitive advantages that big data algorithms have brought to NetEase Cloud Platform in the field of personalized services and to look forward to the impact that big data algorithms will have on the music industry in the future.