Toward Expressive and Scalable Sponsored Search Auctions

Authors:
David J. Martin;Johannes Gehrke;Joseph Y. Halpern
Affiliations:
Department of Computer Science, Cornell University, Ithaca, NY, USA. djm@cs.cornell.edu;Department of Computer Science, Cornell University, Ithaca, NY, USA. johannes@cs.cornell.edu;Department of Computer Science, Cornell University, Ithaca, NY, USA. halpern@cs.cornell.edu
Venue:
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Year:
2008

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Abstract

Internet search results are a growing and highly profitable advertising platform. Search providers auction advertising slots to advertisers on their search result pages. Due to the high volume of searches and the users' low tolerance for search result latency, it is imperative to resolve these auctions fast. Current approaches restrict the expressiveness of bids in order to achieve fast winner determination, which is the problem of allocating slots to advertisers so as to maximize the expected revenue given the advertisers' bids. The goal of our work is to permit more expressive bidding, thus allowing advertisers to achieve complex advertising goals, while still providing fast and scalable techniques for winner determination.