Translations:Wide & Deep Learning for Recommender Systems/28/en

Wide & Deep became one of the canonical reference architectures for industrial click-through-rate (CTR) prediction and ranking, alongside Factorization Machines and the deep CTR models that followed. The pattern of pairing a memorization-friendly linear branch with a generalization-friendly deep branch motivated successors such as DeepFM, Deep & Cross Network, and xDeepFM, which automate the cross-feature engineering that the wide branch still relies on.