NCS4CVR: Neuron-Connection Sharing for Multi-Task Learning in Video Conversion Rate Prediction

Understand

Click-through rate (CTR) and post-click conversion rate (CVR) predictions are two fundamental modules in industrial ranking systems such as recommender systems, advertising, and search engines.

• Since CVR involves much fewer samples than CTR (known as the CVR data sparsity problem), most of the existing works try to leverage CTR&CVR multi-task learning to improve CVR performance.
• However, typical coarse-grained sub-network/layer sharing methods may introduce conflicts and lead to performance degradation, since not every neuron or neuron connection in one layer should be shared between CVR and CTR tasks.
• This is because users may have different fine-grained content feature preferences between deep consumption and click behavior, represented by CVR and CTR, respectively.