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Auction mechanisms for efficient advertisement selection on public display

Auction mechanisms for efficient advertisement selection on public display
Auction mechanisms for efficient advertisement selection on public display
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 benchmarked 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 ofBluetooth detection, outperforms these two methods by up to 64%.
0922-6389
285-289
IOS Press
Payne, Terry R.
09574f42-3cbc-43d3-86c2-2f96eb6319a0
David, Esther
f26eef58-473c-451b-bbd7-ae39ebb09496
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Sharifi, Matthew
a3be6301-0a4a-4826-87df-6aa3e8485980
Payne, Terry R.
09574f42-3cbc-43d3-86c2-2f96eb6319a0
David, Esther
f26eef58-473c-451b-bbd7-ae39ebb09496
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Sharifi, Matthew
a3be6301-0a4a-4826-87df-6aa3e8485980

Payne, Terry R., David, Esther, Jennings, N.R. and Sharifi, Matthew (2006) Auction mechanisms for efficient advertisement selection on public display. In ECAI 2006, 17th European Conference on Artificial Intelligence. vol. 141, IOS Press. pp. 285-289 .

Record type: Conference or Workshop Item (Paper)

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 benchmarked 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 ofBluetooth detection, outperforms these two methods by up to 64%.

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Published date: 2006
Venue - Dates: European Conference on Artificial Intelligence, Italy, 2006-08-27 - 2006-08-31
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 262363
URI: http://eprints.soton.ac.uk/id/eprint/262363
ISSN: 0922-6389
PURE UUID: e5d0ff1c-7cc2-4b5e-ab87-2cf3211152fd

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Date deposited: 13 Apr 2006
Last modified: 07 Apr 2020 16:37

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