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In this work, we study the guaranteed delivery model which is widely used inonline display advertising. In the guaranteed delivery scenario, ad exposures(which are also called impressions in some works) to users are guaranteed bycontracts signed in advance between advertisers and publishers. A crucialproblem for the advertising platform is how to fully utilize the valuable usertraffic to generate as much as possible revenue.  Different from previous works which usually minimize the penalty ofunsatisfied contracts and some other cost (e.g. representativeness), we proposethe novel consumption minimization model, in which the primary objective is tominimize the user traffic consumed to satisfy all contracts. Under this model,we develop a near optimal method to deliver ads for users. The main advantageof our method lies in that it consumes nearly as least as possible user trafficto satisfy all contracts, therefore more contracts can be accepted to producemore revenue. It also enables the publishers to estimate how much user trafficis redundant or short so that they can sell or buy this part of traffic in bulkin the exchange market. Furthermore, it is robust with regard to prioriknowledge of user type distribution. Finally, the simulation shows that ourmethod outperforms the traditional state-of-the-art methods.

Efficient Delivery Policy to Minimize User Traffic Consumption in Guaranteed Advertising