论文标题
具有分布式求解算法的动态储备价格设计
Dynamic Reserve Price Design with Distributed Solving Algorithm
论文作者
论文摘要
赞助搜索中的意外广告项目可能会减少用户对有机搜索的依赖，从而导致电子商务平台的隐藏成本。为了解决这个问题并促进可持续增长，我们提出了一种动态的储备价格设计，将隐藏成本纳入拍卖机制中，以确定是否出售流量，从而确保收入与用户体验之间保持平衡的关系。我们的动态储备价格设计框架通过最大程度地降低对用户体验的影响，同时维持广告商的长期激励措施以真实地揭示其估值，从而优化了流量销售。此外，我们引入了一种分布式算法，能够在生产环境中计算具有十亿个尺度数据的储备价格。涉及离线评估和在线A/B测试的实验表明，此方法是简单有效的，使其适合于工业生产。该方法已经在生产环境中完全部署。
Unexpected advertising items in sponsored search may reduce users' reliance on organic search, resulting in hidden cost for the e-commerce platform. To address this problem and promote sustainable growth, we propose a dynamic reserve price design that incorporates the hidden cost into the auction mechanism to determine whether to sell the traffic, thereby ensuring a balanced relationship between revenue and user experience. Our dynamic reserve price design framework optimizes traffic sales by minimizing impacts on user experience while maintaining long-term incentives for advertisers to reveal their valuations truthfully. Furthermore, we introduce a distributed algorithm capable of computing reserve prices with billion-scale data in the production environment. Experiments involving offline evaluations and online A/B testing demonstrate that this method is simple and efficient, making it suitable for use in industrial production. This method has already been fully deployed in the production environment.
