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Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting (Paperback)
Loot Price: R2,223
Discovery Miles 22 230
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Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting (Paperback)
Series: Foundations and Trends in Information Retrieval
Expected to ship within 10 - 15 working days
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Online advertising is now one of the fastest advancing areas in the
IT industry. In display and mobile advertising, the most
significant technical development in recent years is the growth of
Real-Time Bidding (RTB), which facilitates a real-time auction for
a display opportunity. 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 number 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 optimization in RTB also brings new
research opportunities in information retrieval, data mining,
machine learning and other related fields. Despite its rapid growth
and huge potential, many aspects of RTB remain unknown to the
research community for a variety of reasons. This monograph offers
insightful knowledge of real-world systems, to bridge the gaps
between industry and academia, and to provide an overview of the
fundamental infrastructure, algorithms, and technical and research
challenges of the new frontier of computational advertising. The
topics covered include user response prediction, bid landscape
forecasting, bidding algorithms, revenue optimization, statistical
arbitrage, dynamic pricing, and ad fraud detection. This is an
invaluable text for researchers and practitioners alike. Academic
researchers will get a better understanding of the real-time online
advertising systems currently deployed in industry. While industry
practitioners are introduced to the research challenges, the state
of the art algorithms and potential future systems in this field.
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