Deep Interest Evolution Network for Click-Through Rate Prediction

Understand

Click-through rate~(CTR) prediction, whose goal is to estimate the probability of the user clicks, has become one of the core tasks in advertising systems.

• For CTR prediction model, it is necessary to capture the latent user interest behind the user behavior data.
• Besides, considering the changing of the external environment and the internal cognition, user interest evolves over time dynamically.
• There are several CTR prediction methods for interest modeling, while most of them regard the representation of behavior as the interest directly, and lack specially modeling for latent interest behind the concrete behavior.