How Bing predicts the CTR of ads

An upcoming ICML 2010 paper, "Web-Scale Bayesian Click-Through Rate Prediction for Sponsored Search Advertising in Microsoft’s Bing Search Engine", describes the algorithm actually used in the Bing search engine to predict the clickthrough rates of ads.

From the paper:

Recognising the importance of CTR estimation for online advertising ... Bing/adCenter decided to run a competition to entice people across the company to develop the most accurate and scalable CTR predictor.

The algorithm described in this publication tied for first place in the first competition and won the subsequent competition based on prediction accuracy. As a consequence, it was chosen to replace Bing's previous CTR prediction algorithm, a transition that was completed in the summer of 2009.

The paper goes on to describe why the problem is important, the algorithm used, and some of the nastiness of getting something that works in the lab to run on the live site.

Don't miss the tidbit at the end where they say that they are "investigating the use of more powerful models, such as the feature-based collaborative filtering method Matchbox (Stern, Herbrich, & Graepel, 2009) for latent feature discovery and personalisation."