Uber Improves Restaurant Recommendations Using Real-Time Signals and Listwise Ranking

Uber updates its Uber Eats Home Feed recommendation system using near real-time user sequence features and a Generative Recommender model. The system evolves from hand-crafted features to transformer-based sequence modeling, reduces feature freshness from 24 hours to seconds, and shifts from pointwise scoring to listwise GenRec for improved contextual ranking and real-time personalization. By Leela Kumili

Source: InfoQ — read the full report at the original publisher.

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