  We present a new algorithm for behavioral targeting of banner advertisements.
We record different user's actions such as clicks, search queries and page
views. We use the collected information on the user to estimate in real time
the probability of a click on a banner. A banner is displayed if it either has
the highest probability of being clicked or if it is the one that generates the
highest average profit.
