A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy

Afshar, Reza Refaei; Zhang, Yingqian; Fırat, Murat; Kaymak, Uzay

doi:10.5220/0007395502560265

Cited by 14 publications

(20 citation statements)

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“…Sellers or publishers of advertisements aim to maximize the revenue obtained through online advertising. In this paper, we propose a method to select the most profitable ad network for each ad request that is built upon our previous work [1]. The proposed method consists of two parts: a prediction model and a reinforcement learning modeling.…”

Section: School Of Industrial Engineering Eindhoven University Of Tementioning

confidence: 99%

“…Therefore, a dynamic ordering is necessary. In [1] we proposed a reinforcement learning method to derive optimal ordering of ad networks. In this paper, we extend this approach and explore the significance of each part of the method.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the first step, a prediction model predicts a revenue value for all possible ad request-ad network pairs. In this paper, unlike our recent work [1], we do not start from RL and use prediction model as approximation. Instead, we can state that it is natural to use machine learning methods to build a prediction model in order to estimate whether ad requests will be successful if a specific ad network is used.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, in this paper, our goal is to investigate the "good use" of the prediction model for our particular optimization problem. On one hand, the prediction model could be used as an ordering strategy and the ordering is based on the success probabilities [1]. On the other hand, the prediction model can provide initial revenue for RL step to improve the revenue estimation.…”

Section: Introductionmentioning

confidence: 99%

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A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy

Afshar

Zhang

Fırat

et al. 2019

2019 IEEE Conference on Computational Intelligence for Financial Engineering &Amp; Economics (CIFEr)

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Section: School Of Industrial Engineering Eindhoven University Of Tementioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy

Afshar

Zhang

Fırat

et al. 2019

2019 IEEE Conference on Computational Intelligence for Financial Engineering &Amp; Economics (CIFEr)

Self Cite

View full text Add to dashboard Cite

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“…In this paper we focus on reserve price optimization wihtin a single SSP, but there are also studies (e.g. [11], [12], [13], [14]) that consider optimization problems with multiple SSPs and guaranteed contracts.…”

Section: Related Literaturementioning

confidence: 99%