Towards Deeper, Lighter and Interpretable Cross Network for CTR Prediction
Fangye Wang,
Hansu Gu,
Dongsheng Li
et al.
Abstract:Click Through Rate (CTR) prediction plays an essential role in recommender systems and online advertising. It is crucial to effectively model feature interactions to improve the prediction performance of CTR models. However, existing methods face three significant challenges. First, while most methods can automatically capture high-order feature interactions, their performance tends to diminish as the order of feature interactions increases. Second, existing methods lack the ability to provide convincing inter… Show more
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