Paper
16 June 2023 Construction of personalized recommendation system for pop music based on big data analysis
Wenhua Xiang, Chunqiu Wang, Xucheng Geng
Author Affiliations +
Proceedings Volume 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023); 127030Y (2023) https://doi.org/10.1117/12.2682981
Event: Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 2023, Hong Kong, China
Abstract
One of the main purposes of music recommendation system is how to recommend the songs that users expect from the massive song data. Most people will use the search function of the software to search for some singers or favorite song categories they have known before. However, the search results do not consider that users are different individuals and have different preferences for songs, which leads to low user satisfaction. Driven by big data, this article proposes a individuation recommendation algorithm for pop music based on deep learning. At present, the music resources on the Internet are extremely rich, and users of various music platforms are facing the troubles of too many kinds of music and difficult to express their emotions while enjoying the leisure time brought by music. By analyzing the music files in the system and the massive user behavior records saved, the user's interest preferences are obtained, and personalized music service content is provided to users. The simulation results show that the individuation recommendation algorithm of pop music in this article is better than the traditional Collaborative Filtering (CF) in recommendation accuracy and user rating.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wenhua Xiang, Chunqiu Wang, and Xucheng Geng "Construction of personalized recommendation system for pop music based on big data analysis", Proc. SPIE 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 127030Y (16 June 2023); https://doi.org/10.1117/12.2682981
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KEYWORDS
Data analysis

Data modeling

Emotion

Internet

Deep learning

Fermium

Mining

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