| Bid optimization for broad match ad auctions |
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International World Wide Web Conference
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Proceedings of the 18th international conference on World wide web
table of contents
Madrid, Spain
SESSION: Internet monetization/session: sponsored search
table of contents
Pages 231-240
Year of Publication: 2009
ISBN:978-1-60558-487-4
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Authors
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Eyal Even Dar
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Google Research, New York, NY, USA
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Vahab S. Mirrokni
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Google Research, New York, NY, USA
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S. Muthukrishnan
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Google Research, New York, NY, USA
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Yishay Mansour
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Google Research and Tel-Aviv University, New York, NY, USA
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Uri Nadav
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Tel-Aviv University, Tel-Aviv, Israel
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Downloads (6 Weeks): 23, Downloads (12 Months): 119, Citation Count: 0
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ABSTRACT
Ad auctions in sponsored search support "broad match" that allows an advertiser to target a large number of queries while bidding only on a limited number. While giving more expressiveness to advertisers, this feature makes it challenging to optimize bids to maximize their returns: choosing to bid on a query as a broad match because it provides high profit results in one bidding for related queries which may yield low or even negative profits. We abstract and study the complexity of the {\em bid optimization problem} which is to determine an advertiser's bids on a subset of keywords (possibly using broad match) so that her profit is maximized. In the query language model when the advertiser is allowed to bid on all queries as broad match, we present a linear programming (LP)-based polynomial-time algorithm that gets the optimal profit. In the model in which an advertiser can only bid on keywords, ie., a subset of keywords as an exact or broad match, we show that this problem is not approximable within any reasonable approximation factor unless P=NP. To deal with this hardness result, we present a constant-factor approximation when the optimal profit significantly exceeds the cost. This algorithm is based on rounding a natural LP formulation of the problem. Finally, we study a budgeted variant of the problem, and show that in the query language model, one can find two budget constrained ad campaigns in polynomial time that implement the optimal bidding strategy. Our results are the first to address bid optimization under the broad match feature which is common in ad auctions.
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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