Deep Learning Applications in Meituan‑Dianping Recommendation System
The paper describes Meituan‑Dianping’s two‑stage recommendation pipeline—recall and ranking—and how a Wide & Deep neural architecture, enriched with extensive user, item, and context features and trained with Adam and cross‑entropy loss, significantly boosts CTR and recommendation novelty, with future plans to add RNNs and reinforcement learning.
