<ul><li>Researchers have developed a multi-selection model for answering differentially private queries in recommendation systems.</li><li>The model allows the server to send multiple recommendations and a 'local model' to the user.</li><li>Users can then use the local model to select the item that best matches their private features.</li><li>The multi-selection paradigm achieves an average recommendation utility of approximately 97% while maintaining local differential privacy.</li></ul>

Multi-Selection for Recommendation Systems

Discover more