  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.
