实时竞价:计算广告研究的新前沿

Jun Wang, Shuai Yuan
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引用次数: 58

摘要

在展示广告和移动广告领域,近年来最重要的发展是实时竞价(RTB),它允许一次在一个广告印象中实时销售和购买。从那时起,RTB通过在大量可用库存中扩展购买过程,从根本上改变了数字营销的格局。RTB对自动化、集成和优化的需求为IR/DM/ML领域带来了新的研究机会。然而,尽管RTB发展迅速,潜力巨大,但由于种种原因,研究界对RTB的许多方面仍知之甚少。在本教程中,我们邀请了来自在线广告行业的杰出演讲者,我们的目标是带来来自现实世界系统的深刻知识,以弥合差距,并提供基本基础设施,算法,以及计算广告这一新前沿的技术和研究挑战的概述。我们还将向研究人员介绍公开可用的数据集、工具和平台,以便他们可以快速上手。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Bidding: A New Frontier of Computational Advertising Research
In display and mobile advertising, the most significant development in recent years is the Real-Time Bidding (RTB), which allows selling and buying in real-time one ad impression at a time. Since then, RTB has fundamentally changed the landscape of the digital marketing by scaling the buying process across a large number of available inventories. The demand for automation, integration and optimisation in RTB brings new research opportunities in the IR/DM/ML fields. However, despite its rapid growth and huge potential, many aspects of RTB remain unknown to the research community for many reasons. In this tutorial, together with invited distinguished speakers from online advertising industry, we aim to bring the insightful knowledge from the real-world systems to bridge the gaps and provide an overview of the fundamental infrastructure, algorithms, and technical and research challenges of this new frontier of computational advertising. We will also introduce to researchers the datasets, tools, and platforms which are publicly available thus they can get hands-on quickly.
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