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Selling ad campaigns: online algorithms with cancellations
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Electronic Commerce archive
Proceedings of the tenth ACM conference on Electronic commerce table of contents
Stanford, California, USA
SESSION: Session 2 table of contents
Pages 61-70  
Year of Publication: 2009
ISBN:978-1-60558-458-4
Authors
Moshe Babaioff  Microsoft Research - Silicon Valley, Mountain View, CA, USA
Jason D. Hartline  Northwestern University, Evanston, IL, USA
Robert D. Kleinberg  Cornell University, Ithaca, NY, USA
Sponsors
ACM: Association for Computing Machinery
SIGEcom: ACM Special Interest Group on Electronic Commerce
Publisher
ACM  New York, NY, USA
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ABSTRACT

We study online pricing problems in markets with cancellations, i.e., markets in which prior allocation decisions can be revoked, but at a cost. In our model, a seller receives requests online and chooses which requests to accept, subject to constraints on the subsets of requests which may be accepted simultaneously. A request, once accepted, can be canceled at a cost which is a fixed fraction of the request value. This scenario models a market for web advertising campaigns, in which the buyback cost represents the cost of canceling an existing contract.

We analyze a simple constant-competitive algorithm for a single-item auction in this model, and we prove that its competitive ratio is optimal among deterministic algorithms, but that the competitive ratio can be improved using a randomized algorithm. We then model ad campaigns using knapsack domains, in which the requests differ in size as well as in value. We give a deterministic online algorithm that achieves a bi-criterion approximation in which both approximation factors approach 1 as the buyback factor and the size of the maximum request approach 0. We show that the bi-criterion approximation is unavoidable for deterministic algorithms, but that a randomized algorithm is capable of achieving a constant competitive ratio. Finally, we discuss an extension of our randomized algorithm to matroid domains (in which the sets of simultaneously satisfiable requests constitute the independent sets of a matroid) as well as present results for domains in which the buyback factor of different requests varies.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Babaioff, M., Hartline, J.D., and Kleinberg, R. Online algorithms with buyback. In Proc. 4th Workshop on Ad Auctions (2008).
 
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Buchbinder, N., Jain, K., and Naor, J.S. Online primal-dual algorithms for maximizing ad-auctions revenue. In ESA (2007), pp. 253--264.
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Constantin, F., Feldman, J., Muthukrishnan, S., and Pál, M. An online mechanism for ad slot reservations with cancellations. In Proc. 4th Workshop on Ad Auctions (2008).
 
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Sandholm, T., and Lesser, V.R. Advantages of a leveled commitment contracting protocol. In AAAI/IAAI, Vol. 1 (1996), pp. 126--133.

Collaborative Colleagues:
Moshe Babaioff: colleagues
Jason D. Hartline: colleagues
Robert D. Kleinberg: colleagues