PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Advertising Campaigns Management: Should We Be Greedy?
sertan girgin, Jeremie Mary, Philippe Preux and olivier nicol
In: 10th IEEE International Conference on Data Mining (ICDM), 14-17 Dec 2010, Sydney, Australia.

Abstract

We consider the problem of displaying advertisements on web pages in the ``cost per click'' model, which necessitates to learn the appeal of visitors for the different advertisements in order to maximize the revenue. In a realistic context, the advertisements have constraints such as a certain number of clicks to draw, as well as a lifetime. This problem is thus inherently dynamic, and intimately combines combinatorial and statistical issues. To set the stage, it is also noteworthy that we deal with very rare events of interest, since the base probability of one click is in the order of $10^{-4}$. We introduce an adaptive policy learning algorithm based on linear programming, and investigate its performance through simulations on a realistic model designed with an important commercial web actor.

EPrint Type:Conference or Workshop Item (Paper)
Additional Information:An extended version of this paper is available as the INRIA Reseach Report 7388, at http://hal.inria.fr/inria-00519694/en/
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:7033
Deposited By:Philippe Preux
Deposited On:12 December 2010