I will talk about an optimal online algorithm for Internet Ad markets, such as Google's AdWords market. Although this result was obtained over a decade ago when the algorithmic and economic/game-theoretic issues of this marketplace were just being understood, its impact is becoming clear only in recent years. Our result addresses a central algorithmic issue underlying this marketplace: how to match query keywords to advertisers so as to maximize Google's revenue. I will give an overview of the novel LP-based techniques that led to this result and the simple heuristic, of bid scaling, that is suggested by our algorithm which meets one of the key requirements that Google should be able to make query allocations in real time. These ideas have been widely adopted by Google and other search engine companies. Purely theoretical work, from the 1990s, on the online bipartite matching problem greatly benefitted our work. The latter problem, while mathematically clean and elegant, appears to have no applications. On the other hand, the multi-billion dollar online ad industry has become the key source of revenues for several Internet companies. For algorithms designers, this a very happy story of practical impact from rich theory.

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