Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks

Understand

Click prediction is one of the fundamental problems in sponsored search.

• Most of existing studies took advantage of machine learning approaches to predict ad click for each event of ad view independently.
• However, as observed in the real-world sponsored search system, user's behaviors on ads yield high dependency on how the user behaved along with the past time, especially in terms of what queries she submitted, what ads she clicked or ignored, and how long she spent on the landing pages of clicked ads, etc.
• Inspired by these observations, we introduce a novel framework based on Recurrent Neural Networks (RNN).