An optimal algorithm for on-line bipartite matching
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Selected Topics in Column Generation
Operations Research
Optimal delivery of sponsored search advertisements subject to budget constraints
Proceedings of the 8th ACM conference on Electronic commerce
The adwords problem: online keyword matching with budgeted bidders under random permutations
Proceedings of the 10th ACM conference on Electronic commerce
Optimal online assignment with forecasts
Proceedings of the 11th ACM conference on Electronic commerce
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This paper proposes a new unified optimization framework combining pay-per-click auctions and guaranteed delivery in sponsored search. Advertisers usually have different (and sometimes mixed) marketing goals: brand awareness and direct response. Different mechanisms are good at addressing different goals, e.g., guaranteed delivery was often used to build brand awareness and pay-per-click auctions was widely used for direct marketing. Our new method accommodates both in a unified framework, with the search engine revenue as an optimization objective. In this way, we can target a guaranteed number of ad clicks (or impressions) per campaign for advertisers willing to pay a premium and enable keyword auctions for all others. Specifically, we formulate this joint optimization problem using linear programming and a column generation strategy for efficiency. To select the best column (a ranked list of ads) given a query, we propose a novel dynamic programming algorithm that takes the special structure of the ad allocation and pricing mechanisms into account. We have tested the proposed framework and the algorithms on real ad data obtained from a commercial search engine. The results demonstrate that our proposed approach can outperform several baselines in guaranteeing the number of clicks for the given advertisers, and in increasing the total revenue for the search engine.