Click-through rate prediction in online advertising: A literature review
Y Yang, P Zhai - Information Processing & Management, 2022 - Elsevier
Predicting the probability that a user will click on a specific advertisement has been a
prevalent issue in online advertising, attracting much research attention in the past decades …
prevalent issue in online advertising, attracting much research attention in the past decades …
Product-based neural networks for user response prediction
Predicting user responses, such as clicks and conversions, is of great importance and has
found its usage inmany Web applications including recommender systems, websearch and …
found its usage inmany Web applications including recommender systems, websearch and …
Display advertising with real-time bidding (RTB) and behavioural targeting
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 …
as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates …
Predicting winning price in real time bidding with censored data
In the aspect of a Demand-Side Platform (DSP), which is the agent of advertisers, we study
how to predict the winning price such that the DSP can win the bid by placing a proper …
how to predict the winning price such that the DSP can win the bid by placing a proper …
Multi-objective grammatical evolution of decision trees for mobile marketing user conversion prediction
The worldwide adoption of mobile devices is raising the value of Mobile Performance
Marketing, which is supported by Demand-Side Platforms (DSP) that match mobile users to …
Marketing, which is supported by Demand-Side Platforms (DSP) that match mobile users to …
Ibex: Privacy-preserving ad conversion tracking and bidding
This paper introduces Ibex, an advertising system that reduces the amount of data that is
collected on users while still allowing advertisers to bid on real-time ad auctions and …
collected on users while still allowing advertisers to bid on real-time ad auctions and …
Bid-aware gradient descent for unbiased learning with censored data in display advertising
In real-time display advertising, ad slots are sold per impression via an auction mechanism.
For an advertiser, the campaign information is incomplete---the user responses (eg, clicks or …
For an advertiser, the campaign information is incomplete---the user responses (eg, clicks or …
Attribution modeling increases efficiency of bidding in display advertising
E Diemert, J Meynet, P Galland, D Lefortier - Proceedings of the ADKDD' …, 2017 - dl.acm.org
Predicting click and conversion probabilities when bidding on ad exchanges is at the core of
the programmatic advertising industry. Two separated lines of previous works respectively …
the programmatic advertising industry. Two separated lines of previous works respectively …
Deep landscape forecasting in multi-slot real-time bidding
Real-Time Bidding (RTB) has shown remarkable success in display advertising and has
been employed in other advertising scenarios, eg, sponsored search advertising with …
been employed in other advertising scenarios, eg, sponsored search advertising with …
Deep censored learning of the winning price in the real time bidding
We generalize the winning price model to incorporate the deep learning models with
different distributions and propose an algorithm to learn from the historical bidding …
different distributions and propose an algorithm to learn from the historical bidding …