Abstract
With the development of the Internet, people can get information about the songs they need through computers, mobile phones, etc. in their lives. In the field of vocal music, people usually use computers for data processing and analysis, and music websites and other related network technologies provide us with functions such as resource sharing and collaborative filtering. This article mainly introduces the popular vocal personalized recommendation system based on particle swarm algorithm. The purpose is to use Internet technology for personalized design, so that the music public can hear the music they want without searching. This article mainly uses case analysis, experiment and survey methods to study the recommendation system, and uses related algorithms to calculate the results of the system. The experimental results show that the recommendation system designed in this paper is in line with the public's pursuit, and has certain accuracy and recommendation significance.
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References
Zeng, X., et al.: Research on subjective evaluation indexes of music recommendation system-taking netease cloud music as an example. News and Communication Review 6, 94–107 (2019)
Liang, Y.: Application research of music personalized recommendation system based on big data analysis. Artwork Jian 7Z, 153–154 (2019)
Li, Z., Zeng, D., Zhang, Z.: Research on music recommendation system based on collaborative filtering and music mood. Industrial Control Computer 31(07), 130–131 and 134 (2018)
Zhi, G., Xi, S.: Multi-modal music recommendation system. Journal of Nanjing University of Information Technology (Natural Science Edition) 11(59 and 01), 72–80 (2019)
Zhu, Z., Tian, J., Lin, J.: Design of personalized music recommendation system based on user location in big data environment. Wireless Internet Technology 16(02), 85–86 (2019)
Zhang, R.: Real-time music recommendation system based on scene changes. Communication World 340(09), 237–238 (2018)
Wu, Y., Liu, D., Xu, X.: Real-time music recommendation system design based on two-way sentiment analysis. Journal of Dalian Nationalities University 19(001), 76–79 (2017)
Han, Y.: Design and implementation of music recommendation system based on graph database. Digital World 000(011), 38–42 (2017)
Li, T., Fu, D.: Automatic implicit scoring music dual recommendation system based on collaborative filtering algorithm. Computer Measurement and Control 26(11), 177–181 (2018)
Talking about the new music broadcasting model combining the recommendation system and the typed radio station. Radio and Television Information 322(02), 78–81 (2019)
Liu, J.: Analyze the status quo and development trend of Chinese pop music. Tomorrow Fashion 000(006), 136–137 (2018)
Cui, J., Che, M.: Intelligent recommendation system and empirical analysis of optimization algorithm based on multi-class support vector machine. Computer Engineering and Science 41(01), 153–160 (2019)
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Fan, X. (2022). Popular Vocal Music Recommendation System Based on Particle Swarm Algorithm. In: Sun, S., Hong, T., Yu, P., Zou, J. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2021. Lecture Notes in Electrical Engineering, vol 895. Springer, Singapore. https://doi.org/10.1007/978-981-19-4775-9_68
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DOI: https://doi.org/10.1007/978-981-19-4775-9_68
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