English

Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

Computer Science and Game Theory 2017-07-18 v2

Abstract

The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user's visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection.

Keywords

Cite

@article{arxiv.1610.03013,
  title  = {Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting},
  author = {Jun Wang and Weinan Zhang and Shuai Yuan},
  journal= {arXiv preprint arXiv:1610.03013},
  year   = {2017}
}

Comments

A 122-page monograph about RTB display advertising, which will be published on Now Publisher in July 2017