Feb 28, 2020 · Artificial Intelligence

Bayesian Smoothing and Key-Value Memory Networks for Click-Through Rate Prediction in Recommendation Systems

This article presents a Bayesian smoothing approach to alleviate cold-start problems in click-through rate estimation, introduces key-value memory networks to incorporate prior knowledge, and proposes methods to convert continuous features into dictionary embeddings for deep learning models in recommendation systems.

Deep Learningclick-through ratecontinuous feature embedding

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Bayesian Smoothing and Key-Value Memory Networks for Click-Through Rate Prediction in Recommendation Systems