Personalized audiobook recommendations using graph neural networks
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Introduction
Spotify is the most popular music-streaming app in the world. In addition to songs and albums, Spotify has a great collection of podcasts and talk shows. They have recently introduced audiobooks in their app. Like any other offering, Spotify wanted to ensure that its audiobook recommendations catered to user’s preferences. Hence, they developed a Graph Neural Network-based recommendation algorithm to personalize audiobook recommendations.
This article discusses the challenges Spotify faced in delivering personalized audiobook recommendations and the exploratory data analyses conducted to address them. It explores Spotify’s innovative solution: a two-tower graph neural network model designed to enhance audiobook personalization.
Challenges
As audiobooks were a recent addition to Spotify’s content library, they faced some challenges —
- There was a data scarcity issue as the content type was newly introduced. There were fewer user interactions for audiobooks compared to other content types. Many users were unaware of audiobooks on Spotify.