论文标题
一个新颖的拍卖系统，用于在实时招标中选择广告
A novel auction system for selecting advertisements in Real-Time bidding
论文作者
论文摘要
实时竞标是一种新的互联网广告系统，近年来已经非常受欢迎。该系统就像全球拍卖一样工作，广告商在出版商的广告插槽中竞标展示其印象。选择哪种广告商赢得每笔拍卖的最受欢迎的系统是广义的第二价拍卖，在该拍卖中，广告广告商提供了最大的胜利，并以第二大赌注的价格收取。在本文中，我们提出了一种新方法，不仅考虑了经济方面，而且还考虑了广告系统功能的其他相关因素。我们考虑的因素包括可以给每个广告商带来的好处，广告转换的可能性，访问欺诈性的可能性，参与RTB的网络的平衡程度以及广告商没有支付的费用。此外，我们提出了一种基于遗传算法的方法，以优化每个广告商的选择。我们还进行了一些实验，以将所提出模型的性能与著名的广义第二价格方法进行比较。我们认为，这种新方法除了价格外还考虑了更相关的方面，在中长期内为RTB网络提供了更大的好处。
Real-Time Bidding is a new Internet advertising system that has become very popular in recent years. This system works like a global auction where advertisers bid to display their impressions in the publishers' ad slots. The most popular system to select which advertiser wins each auction is the Generalized second-price auction in which the advertiser that offers the most wins the bet and is charged with the price of the second largest bet. In this paper, we propose an alternative betting system with a new approach that not only considers the economic aspect but also other relevant factors for the functioning of the advertising system. The factors that we consider are, among others, the benefit that can be given to each advertiser, the probability of conversion from the advertisement, the probability that the visit is fraudulent, how balanced are the networks participating in RTB and if the advertisers are not paying over the market price. In addition, we propose a methodology based on genetic algorithms to optimize the selection of each advertiser. We also conducted some experiments to compare the performance of the proposed model with the famous Generalized Second-Price method. We think that this new approach, which considers more relevant aspects besides the price, offers greater benefits for RTB networks in the medium and long-term.
