Auction Mechanisms for Efficient Advertisement Selection on Public Displays

  • Authors:

  • Terry Payne;Ester David;Nicholas R. Jennings;Matthew Sharifi

  • Affiliations:

  • School of Electronics and Computer Science, University of Southampton, UK, email: {trp, ed, nrj, mns203}@ecs.soton.ac.uk;School of Electronics and Computer Science, University of Southampton, UK, email: {trp, ed, nrj, mns203}@ecs.soton.ac.uk;School of Electronics and Computer Science, University of Southampton, UK, email: {trp, ed, nrj, mns203}@ecs.soton.ac.uk;School of Electronics and Computer Science, University of Southampton, UK, email: {trp, ed, nrj, mns203}@ecs.soton.ac.uk

  • Venue:
  • Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
  • Year:
  • 2006

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Abstract

Public electronic displays can be used as an advertising medium when space is a scarce resource, and it is desirable to expose many adverts to as wide an audience as possible. Although the efficiency of such advertising systems can be improved if the display is aware of the identity and interests of the audience, this knowledge is difficult to acquire when users are not actively interacting with the display. To this end, we present BluScreen, an intelligent public display, which selects and displays adverts in response to users detected in the audience. Here, users are identified and their advert viewing history tracked, by detecting any Bluetooth-enabled devices they are carrying (e.g. phones, PDAs, etc.). Within BluScreen we have implemented an agent system that utilises an auction-based marketplace to efficiently select adverts for the display, and deployed this within an installation in our Department. We demonstrate, by means of an empirical evaluation, that the performance of this auction-based mechanism when used with our proposed bidding strategy, efficiently selects the best adverts in response to the audience presence. We bench-marked our advertising method with two other commonly applied selection methods for displaying adverts on public displays; specifically the Round-Robin and the Random approaches. The results show that our auction-based approach, that utilised the novel use of Bluetooth detection, outperforms these two methods by up to 64%.