Pepelyshev, Andrey ![]() ![]() ![]() |
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Official URL: https://doi.org/10.1007/978-3-319-31266-8_23
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) |
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Date Type: | Published Online |
Status: | Published |
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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