Bidding for Representative Allocations for Display Advertising

Ghosh, Aritra; McAfee, Preston; Papineni, Kishore; Vassilvitskii, Sergei

doi:10.1007/978-3-642-10841-9_20

Cited by 111 publications

(86 citation statements)

References 9 publications

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“…Notice that the solution is feasible because it satisfies constraints (9) and (10). In order to prove optimality it suffices to show that it attains the dual objective value, or that it satisfies the complementary slackness conditions.…”

Section: Subset Nodesmentioning

confidence: 99%

Yield Optimization of Display Advertising with Ad Exchange

et al. 2014

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Abstract. In light of the growing market of Ad Exchanges for the real-time sale of advertising slots, publishers face new challenges in choosing between the allocation of contract-based reservation ads and spot market ads. In this setting, the publisher should take into account the tradeoff between short-term revenue from an Ad Exchange and the long-term benefits of delivering good quality spots to the reservation ads. In this paper, we formalize this combined optimization problem as a stochastic control problem and derive an efficient policy for online ad allocation in settings with general joint distribution over placement quality and exchange bids. We prove asymptotic optimality of this policy in terms of any trade-off between quality of delivered reservation ads and revenue from the exchange, and provide a rigorous bound for its convergence rate to the optimal policy. We also give experimental results on data derived from real publisher inventory, showing that our policy can achieve any Pareto-optimal point on the quality vs. revenue curve. Finally, we study a parametric training-based algorithm in which instead of learning the dual variables from a data sample (as is done in non-parametric training-based algorithms), we learn the parameters of the distribution and construct those dual variables from the learned parameter values. We compare parametric and non-parametric ways to estimate from data both analytically and experimentally in the special case without the ad exchange, and show that though both methods converge to the optimal policy as the sample size grows, our parametric method converges faster, and thus performs better on smaller samples.

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Section: Subset Nodesmentioning

confidence: 99%

Yield Optimization of Display Advertising with Ad Exchange

et al. 2014

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“…While there are many papers that study sponsored search, as well as auctions for the more intricate research area of banner ads (which consists of interactions between many classes of actors, including publishers, advertisers, ad networks, and ad exchanges, e.g., see [16][17][18][19][20]), none of these works consider the problem faced by an MdSE who needs to aggregate information from different types of sources, and ensure that they are adequately compensated. An exception is [2] which considers the problem of merging ads from different sources for federated search.…”

Section: Related Workmentioning

confidence: 99%

An Incentive–Compatible Revenue–Sharing Mechanism for the Economic Sustainability of Multi–domain Search Based on Advertising

et al. 2012

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Abstract. Multi-domain search engines decompose complex queries addressing several issues at a time into sub-queries, and forwards them to one or more domain-specific content providers, typically implemented as Web services. This enables complex searches (e.g., vacation planning, composed of a hotel, flight, and car search), and allows users to receive aggregated and high quality results from a variety of sources. We focus on the design of a revenue sharing mechanism for multi-domain search, considering the general setting in which different actors (content providers, advertising providers, hybrid content+advertising providers, and content integrators) are involved in the search results generation. The design of such a mechanism is paramount for the economic sustainability of multi-domain search. Our revenue sharing mechanism extends the existing sponsored search auctions by supporting heterogeneous participants and allowing the redistribution of monetary values to the different actors.

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“…Display advertising has become one of the most profitable areas of online services, responsible for approximately $24 billion in business [5]. Unlike sponsored search, where textual ads are displayed along the results of a keyword search, display advertising targets specific audiences by showing graphical banner ads on regular content pages.…”

Section: Introductionmentioning

confidence: 99%

“…This has been the standard approach in recent work on the problem (e.g. [2] and [5]). Like these papers, we think of the supply of ads as a 'channel' with an uncertain capacity.…”

Section: Introductionmentioning

confidence: 99%

Optimal delivery in display advertising

Mostagir

2010

2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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In display advertising, a publisher targets a specific audience by displaying ads on content web pages. Because the publisher has little control over the supply of display opportunities, the actual supply of ads that it can sell is stochastic. We consider the problem of optimal ad delivery, where an advertiser requests a certain number of impressions to be displayed by the publisher over a certain time horizon. Time is divided into periods, and in the beginning of each period the publisher chooses a fraction of the still unrealized supply to allocate towards fulfilling the advertiser's demand. The goal is to be able to fulfill the demand at the end of the horizon with minimal costs incurred from penalties associated with shortage or over-delivery of ads. We describe optimal policies that are both simple in structure and easy to implement for several variations of this problem.

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Bidding for Representative Allocations for Display Advertising

Cited by 111 publications

References 9 publications

Yield Optimization of Display Advertising with Ad Exchange

Yield Optimization of Display Advertising with Ad Exchange

An Incentive–Compatible Revenue–Sharing Mechanism for the Economic Sustainability of Multi–domain Search Based on Advertising

Optimal delivery in display advertising

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