How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective

no code implementations • 18 Apr 2024 • Siyi Lin, Chongming Gao, Jiawei Chen, Sheng Zhou, Binbin Hu, Can Wang

Our comprehensive theoretical and empirical investigations lead to two core insights: 1) Item popularity is memorized in the principal singular vector of the score matrix predicted by the recommendation model; 2) The dimension collapse phenomenon amplifies the impact of principal singular vector on model predictions, intensifying the popularity bias.

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