An Expressive Auction Design for Online Display Advertising

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An Expressive Auction Design for Online Display Advertising

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Title: An Expressive Auction Design for Online Display Advertising
Author: Lahaie, Sébastien; Parkes, David C.; Pennock, David

Note: Order does not necessarily reflect citation order of authors.

Citation: Lahaie, Sébastien, David C. Parkes, and David Pennock. 2008. An expressive auction design for online display advertising. In Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence: July 13-17 2008, Chicago, Illinois, ed. American Association for Artificial Intelligence, 108-113. Menlo Park, Calif.: AAAI Press.
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Abstract: We propose an expressive auction design that allows advertisers to specify the kinds of demographics and websites they wish to target within an advertising network. The design allows the network to differentiate impressions according to relevant attributes (e.g., geographic location of the user, topic of the webpage). Advertisers can place bids for different kinds of impressions according to their attributes, and can also specify volume constraints to control exposure. The novelty of the design is a bidding language that admits scalable allocation and pricing algorithms. We discuss the incentive properties of different pricing approaches. We also propose a bidder feedback mechanism to mitigate the complexity of expressive bidding.
Published Version: http://portal.acm.org/citation.cfm?id=1620014
Other Sources: http://www.eecs.harvard.edu/econcs/pubs/lahaie_aaai08.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4000307

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  • FAS Scholarly Articles [7220]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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