AdWords and Generalized On-line Matching
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
The adwords problem: online keyword matching with budgeted bidders under random permutations
Proceedings of the 10th ACM conference on Electronic commerce
Bidding for Representative Allocations for Display Advertising
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Online Ad Assignment with Free Disposal
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Online primal-dual algorithms for maximizing ad-auctions revenue
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Optimal online assignment with forecasts
Proceedings of the 11th ACM conference on Electronic commerce
Online stochastic packing applied to display ad allocation
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Efficient online ad serving in a display advertising exchange
Proceedings of the fourth ACM international conference on Web search and data mining
Yield optimization of display advertising with ad exchange
Proceedings of the 12th ACM conference on Electronic commerce
SHALE: an efficient algorithm for allocation of guaranteed display advertising
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Online allocation of display ads with smooth delivery
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Model Predictive Control for Dynamic Resource Allocation
Mathematics of Operations Research
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Display ads on the Internet are often sold by publishers to advertisers in bundles of thousands or millions of impressions over a particular time period. The ad delivery systems assign ads to pages on behalf of publishers to satisfy these contracts, and at the same time, try to maximize the overall quality of assignment. This is usually modeled in the literature as an online allocation problem, where contracts are represented by overall delivery constraints. However an important aspect of these contracts is missed by the classical formulation: a majority of these contracts are not between advertisers and publishers; a set of publishers is typically represented by a middle-man and advertisers buy inventory from the middle man. As publishers vary in quality and importance, advertisers prefer these publishers differently. Similarly, as the inventory of ads is limited, ad-delivery engine needs to prefer a high-quality publisher over a low quality publisher for supplying ads. We formulate this problem as a hierarchical online matching problem where each incoming impression has a level indicating its importance, and study its theoretical properties. We also design practical solutions to this problem and study their performance on real data sets.