Mechanism Design for Mobile Geo–Location Advertising
Mechanism Design for Mobile Geo–Location Advertising
Mobile geo–location advertising, where mobile ads are targeted based on a user’s location, has been identified as a key growth factor for the mobile market. As with online advertising, a crucial ingredient for their success is the development of effective economic mechanisms. An important difference is that mobile ads are shown sequentially over time and information about the user can be learned based on their movements. Furthermore, ads need to be shown selectively to prevent ad fatigue. To this end, we introduce, for the first time, a user model and suitable economic mechanisms which take these factors into account. Specifically, we design two truthful mechanisms which produce an advertisement plan based on the user’s movements. One mechanism is allocatively efficient, but requires exponential compute time in the worst case. The other requires polynomial time, but is not allocatively efficient. Finally, we experimentally evaluate the trade–off between compute time and efficiency of our mechanisms.
Gatti, Nicola
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Rocco, Marco
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Ceppi, Sofia
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Gerding, Enrico H.
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July 2014
Gatti, Nicola
aceed282-d524-4b1d-9ad8-0685eac20d3a
Rocco, Marco
6ea18fc7-cf26-494d-8d10-1b42c34df7ed
Ceppi, Sofia
d6dd2f1c-c7a4-4ec1-b3d7-82b433ca5bf8
Gerding, Enrico H.
d9e92ee5-1a8c-4467-a689-8363e7743362
Gatti, Nicola, Rocco, Marco, Ceppi, Sofia and Gerding, Enrico H.
(2014)
Mechanism Design for Mobile Geo–Location Advertising.
Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14).
27 - 31 Jul 2014.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Mobile geo–location advertising, where mobile ads are targeted based on a user’s location, has been identified as a key growth factor for the mobile market. As with online advertising, a crucial ingredient for their success is the development of effective economic mechanisms. An important difference is that mobile ads are shown sequentially over time and information about the user can be learned based on their movements. Furthermore, ads need to be shown selectively to prevent ad fatigue. To this end, we introduce, for the first time, a user model and suitable economic mechanisms which take these factors into account. Specifically, we design two truthful mechanisms which produce an advertisement plan based on the user’s movements. One mechanism is allocatively efficient, but requires exponential compute time in the worst case. The other requires polynomial time, but is not allocatively efficient. Finally, we experimentally evaluate the trade–off between compute time and efficiency of our mechanisms.
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Published date: July 2014
Venue - Dates:
Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), 2014-07-27 - 2014-07-31
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 364838
URI: http://eprints.soton.ac.uk/id/eprint/364838
PURE UUID: 7fdebfde-ee45-4070-b4ff-1bc9381f899e
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Date deposited: 12 May 2014 12:11
Last modified: 15 Mar 2024 03:23
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Contributors
Author:
Nicola Gatti
Author:
Marco Rocco
Author:
Sofia Ceppi
Author:
Enrico H. Gerding
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