FLEN: Leveraging Field for Scalable CTR Prediction

Understand

Click-Through Rate (CTR) prediction has been an indispensable component for many industrial applications, such as recommendation systems and online advertising.

• CTR prediction systems are usually based on multi-field categorical features, i.e., every feature is categorical and belongs to one and only one field.
• Modeling feature conjunctions is crucial for CTR prediction accuracy.
• However, it requires a massive number of parameters to explicitly model all feature conjunctions, which is not scalable for real-world production systems.