Recommender Systems over Wireless: Challenges and Opportunities
Linqi Song, Christina Fragouli, Devavrat Shah · 2018
We consider wireless recommender systems that need to learn the user preferences (explore) and use them to accordingly decide what are the most profitable recommendations to make (exploit), under bandwidth constraints. We propose a graph-based scheme that leverages user side information and coding to efficiently exploit and explore over wireless, and evaluate its performance.