Issue |
SHS Web of Conf.
Volume 193, 2024
2024 International Conference on Applied Psychology and Marketing Management (APMM 2024)
|
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Article Number | 01019 | |
Number of page(s) | 4 | |
Section | Business and Economics | |
DOI | https://doi.org/10.1051/shsconf/202419301019 | |
Published online | 06 June 2024 |
Personalized Services Based on Big Data Algorithms—taking Netease Cloud as an Example
France School of Management Engineering, Qingdao University of Technology, Qingdao, Shandong, 266000, China
* Corresponding author: 100524@yzpc.edu.cn
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.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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