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Found 4 papers, 0 papers with code
Modeling Dynamic User Interests: A Neural Matrix Factorization Approach
In recent years, there has been significant interest in understanding users' online content consumption patterns.
Targeting for long-term outcomes
We apply our approach in two large-scale proactive churn management experiments at The Boston Globe by targeting optimal discounts to its digital subscribers with the aim of maximizing long-term revenue.
The Engagement-Diversity Connection: Evidence from a Field Experiment on Spotify
We also observe evidence that our treatment affected streams from sections of Spotify's app not directly affected by the experiment, suggesting that exposure to personalized recommendations can affect the content that users consume organically.
Scalable bundling via dense product embeddings
We develop a new machine-learning-driven methodology for designing bundles in a large-scale, cross-category retail setting.
