Simple and Scalable Response Prediction for Display Advertising
Olivier Chapelle, Eren Manavoglu, Rómer Rosales · ACM Transactions on Intelligent Systems and Technology · 2014
Clickthrough and conversation rates estimation are two core predictions tasks in display advertising. We present in this article a machine learning framework based on logistic regression that is specifically designed to tackle the specifics of display advertising. The resulting system has the following characteristics: It is easy to implement and deploy, it is highly scalable (we have trained it on terabytes of data), and it provides models with state-of-the-art accuracy.