期刊
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
卷 19, 期 11, 页码 1571-1584出版社
IEEE COMPUTER SOC
DOI: 10.1109/TKDE.2007.190640
关键词
web advertisement; banner ads; scheduling; click behavior; knapsack
The increasing popularity of the World Wide Web has made it an attractive medium for advertisers. As more advertisers place Internet advertisements (hereafter also called ads), it has become important for Web site owners to maximize revenue through the optimal selection and placement of these ads. Unlike most previous research, we consider a hybrid pricing model, where the price advertisers pay is a function of 1) the number of exposures of the ad and 2) the number of clicks on the ad. The problem is finding an ad schedule to maximize the Web site revenue under a hybrid pricing model. We formulate two versions of the problem-static and dynamic-and propose a variety of efficient solution techniques that provide near-optimal solutions. In the dynamic version, the schedule of ads is changed based on individual user click behavior. We show by using a theoretical proof under special circumstances and an experimental demonstration under general conditions that a schedule that adapts to the user click behavior consistently outperforms one that does not. We also demonstrate that to benefit from observing the user click behavior, the associated probability parameter need not be estimated accurately. For both of these versions, we examine the sensitivity of the revenue with respect to the model parameters.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据