Abstract
We study the AdWords problem defined by Mehta, Saberi, Vazirani and Vazirani [10]. A search engine company has a set of advertisers who wish to link ads to user queries and issue respective bids. The goal is to assign advertisers to queries so as to maximize the total revenue accrued. The problem can be formulated as a matching problem in a bipartite graph G. We assume that G is a (k, d)-graph, introduced by Naor and Wajc [11]. Such graphs model natural properties on the degrees of advertisers and queries.
As a main result we present a deterministic online algorithm that achieves an optimal competitive ratio. The competitiveness tends to 1, for arbitrary \(k\ge d\), using the standard small-bids assumption where the advertisers’ bids are small compared to their budgets. Hence, remarkably, nearly optimal ad allocations can be computed deterministically based on structural properties of the input. So far competitive ratios close to 1, for the AdWords problem, were only known in probabilistic input models.
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Albers, S., Schubert, S. (2022). Online Ad Allocation in Bounded-Degree Graphs. In: Hansen, K.A., Liu, T.X., Malekian, A. (eds) Web and Internet Economics. WINE 2022. Lecture Notes in Computer Science, vol 13778. Springer, Cham. https://doi.org/10.1007/978-3-031-22832-2_4
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DOI: https://doi.org/10.1007/978-3-031-22832-2_4
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