Auction mechanisms for efficient advertisement selection on public displays

Terry Payne, Ester David, Nicholas R. Jennings, Matthew Sharifi

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

27 Scopus citations

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%.

Original languageEnglish
Title of host publicationECAI 2006
Subtitle of host publication17th European Conference on Artificial Intelligence August 29 - September 1, 2006, Riva del Garda, Italy
EditorsGerhard Brewka, Silvia Coradeschi, Anna Perini, Paolo Traverso
PublisherIOS Press BV
Pages285-289
Number of pages5
ISBN (Print)9781586036423
StatePublished - 2006
Externally publishedYes

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume141
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Bibliographical note

Funding Information:
This research was partially funded through an internal scholarship provided by the School of Electronics and Computer Science.

Funding

This research was partially funded through an internal scholarship provided by the School of Electronics and Computer Science.

FundersFunder number
School of Electronics and Computer Science

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