ICES: Small: Auctions and Optimizations in Ad Exchanges

ICES：小型：广告交易中的拍卖和优化

• 批准号: 1101677
• 负责人: Shanmugavelayu Muthukrishnan
• 金额: $ 39.36万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1101677&HistoricalAwards=false
• 关键词: ICES; Small; Auctions; Optimizations; Ad

Viewers who browse web pages on the Internet are shown display ads such as images and video. Traditionally, web page publishers and advertisers negotiate a priori through sales teams to determine which ads are shown. An emerging way to buy and sell display ads is via automated ad exchanges, which are marketplaces where publishers and advertisers trade ad impressions via real time auctions. This project explores computational, informational and economic aspects of such ad exchange markets. It will abstract suitable models for such markets and study the fundamental challenges, including problems in auction design, online optimization, risk-bounded pricing, real time bidding strategies, and even cryptography. Specific examples include the design of an optimal auction in the presence of a hierarchy of intermediaries who are also auctioneers, determining at each level of this hierarchy which intermediary to call for bids, and proving the integrity of auctions at each level of the hierarchy. Solving these problems requires new methods, concepts and tools from Economics, Finance and Optimization, and Computer Science. Ad exchanges will impact nearly every user on the Internet. Progress on research challenges described here has the potential to directly impact such systems and the experience of nearly every user on the Internet. Further, facing the technical challenges will bring together Computer Scientists and Economists, and also push these disciplines to address very high performance challenges. For example, auction and optimization solutions have to work in tens of milliseconds, the time it takes for users to experience a web page access. This calls for new algorithmic techniques beyond the current start of the art. Finally, a detailed analysis of the role of information in ad exchanges-how much or little information is relevant for the working of the marketplace-is of great interest to Internet users and ultimately the society.

在互联网上浏览网页的观众会看到图像和视频等展示广告。传统上，网页发布商和广告商通过销售团队先验协商来确定显示哪些广告。购买和销售展示广告的一种新兴方式是通过自动广告交易，这是发布商和广告商通过实时拍卖交易广告印象的市场。该项目探讨了此类广告交易市场的计算、信息和经济方面。它将为此类市场抽象出合适的模型，并研究基本挑战，包括拍卖设计、在线优化、风险有限定价、实时竞价策略，甚至密码学方面的问题。具体示例包括在同时也是拍卖师的中间人层次结构存在的情况下设计最佳拍卖，在该层次结构的每个级别确定哪个中间人招标，并在该层次结构的每个级别证明拍卖的完整性。解决这些问题需要经济学、金融与优化以及计算机科学的新方法、概念和工具。广告交易将影响互联网上的几乎每个用户。这里描述的研究挑战的进展有可能直接影响此类系统以及互联网上几乎每个用户的体验。此外，面对技术挑战将使计算机科学家和经济学家聚集在一起，并推动这些学科应对非常高的性能挑战。例如，拍卖和优化解决方案必须在数十毫秒内运行，即用户体验网页访问所需的时间。这需要超越当前技术的新算法技术。最后，对信息在广告交易中的作用的详细分析（有多少信息与市场运作相关）引起了互联网用户乃至整个社会的极大兴趣。