Adaptive designs for optimizing online advertisement campaigns

Pepelyshev, Andrey ORCID: https://orcid.org/0000-0001-5634-5559, Staroselskiy, Yuri and Zhigljavsky, Anatoly Alexandrovich ORCID: https://orcid.org/0000-0003-0630-8279 2016. Adaptive designs for optimizing online advertisement campaigns. Presented at: 11th International Workshop in Model-Oriented Design and Analysis, Hamminkeln, Germany, 12-17 June 2016. Published in: Kunert, Joachim, Muller, Christine H. and Atkinson, Anthony C. eds. mODa 11 - Advances in Model-Oriented Design and Analysis: Proceedings of the 11th International Workshop in Model-Oriented Design and Analysis held in Hamminkeln, Germany, June 12-17, 2016. mODa 11 - Advances in Model-Oriented Design and Analysis, Proceedings of the 11th International Workshop in Model-Oriented Design and Analysis held in Hamminkeln, Germany, June 12-17, 2016. Contributions to Statistics Springer Verlag, pp. 199-208. 10.1007/978-3-319-31266-8_23

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Abstract

We investigate the problem of adaptive targeting for real-time bidding in online advertisement using independent advertisement exchanges. This is a problem of making decisions based on information extracted from large data sets related to previous experience. We describe an adaptive strategy for optimizing the click through rate which is a key criterion used by advertising platforms to measure the efficiency of an advertisement campaign.We also provide some results of statistical analysis of real data.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Mathematics
Subjects:	Q Science > QA Mathematics
Publisher:	Springer Verlag
ISBN:	9783319312644
Date of First Compliant Deposit:	22 April 2016
Date of Acceptance:	6 January 2016
Last Modified:	25 Nov 2024 15:30
URI:	https://orca.cardiff.ac.uk/id/eprint/89511

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