Background Music Recommendation on Short Video Sharing Platforms

Jiawei Chen (), Luo He (), Hongyan Liu (), Yinghui (Catherine) Yang () and Xuan Bi ()
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Jiawei Chen: School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China
Luo He: School of Economics and Management, Tsinghua University, Beijing 100084, China
Hongyan Liu: School of Economics and Management, Tsinghua University, Beijing 100084, China
Yinghui (Catherine) Yang: Graduate School of Management, University of California, Davis, Davis, California 95616
Xuan Bi: Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455

Information Systems Research, 2024, vol. 35, issue 4, 1890-1908

Abstract: On short video sharing platforms, users often choose background music for their videos. In this paper, we study the problem of background music recommendation for short videos on short video sharing platforms. In our recommendation setting, the item (music) is not recommended directly to the user, but to the video created by the user. When making music recommendations for videos, we consider three important players: users, videos, and music. We define a unique background music recommendation problem and design a novel background music recommendation model to address the problem. We propose a model based on the deep learning framework to effectively address the distinctive three-way relationships among users, videos, and music. Our model considers not only the conventional user–music alignment, but also the alignment between videos and music. To evaluate our model, we conduct comprehensive experiments on real-world data collected from one of the most popular short video sharing platforms. Our proposed model significantly outperforms other existing models in recommendation performance. The superiority of our proposed model remains consistent across various scenarios, including cold-start recommendations, data sets with varying density levels, and data sets spanning diverse video categories.

Keywords: recommendation systems; background music recommendation; deep learning (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orisre:v:35:y:2024:i:4:p:1890-1908

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