Wang, J;
Zhang, W;
Yuan, S;
(2017)
Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting.
Foundations and Trends in Information Retrieval
, 11
(4-5)
pp. 297-435.
10.1561/1500000049.
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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.
| Type: | Article |
|---|---|
| Title: | Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1561/1500000049 |
| Publisher version: | http://dx.doi.org/10.1561/1500000049 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1533040 |
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