Privacy preserving frequency capping in internet banner advertising

ABSTRACT

We describe an optimize-and-dispatch approach for delivering pay-per-impression advertisements in online advertising. The platform provider for an advertising network commits to showing advertisers' banner ads while capping the number of advertising message shown to a unique user as the user transitions through the network. The traditional approach for enforcing frequency caps has been to use cross-site cookies to track users. However,cross-site cookies and other tracking mechanisms can infringe on the user privacy. In this paper, we propose a novel linear programming approach that decides when to show an ad to the user based solely on the page currently viewed by the users. We show that the frequency caps are fulfilled in expectation. We show the efficacy of that approach using simulation results.

REFERENCES

• 1: P. Bremaud. Markov Chains. Springer Verlag, 1996.
• 2: John Canny, Collaborative filtering with privacy via factor analysis, Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval, August 11-15, 2002, Tampere, Finland [doi>10.1145/564376.564419]
• 3: ComScore. How on-line advertising works. Technical report, 2008.
• 4: Mukund Deshpande , George Karypis, Selective Markov models for predicting Web page accesses, ACM Transactions on Internet Technology (TOIT), v.4 n.2, p.163-184, May 2004 [doi>10.1145/990301.990304]

INDEX TERMS

Primary Classification:
  G. Mathematics of Computing
  G.3 PROBABILITY AND STATISTICS
      Subjects: Markov processes

General Terms:
Algorithms, Security

Keywords:
privacy, user model