Abstract
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.
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