Abstract
In affiliate marketing, an affiliate offers to handle the marketing effort selling products of other companies. Click-fraud is damaging to affiliate marketers as they increase the cost of internet traffic. There is a need for a solution that has an economic incentive to protect marketers while providing them with data they need to reason about the traffic quality. In our solution, we propose a set of interpretable flags explainable ones to describe the traffic. Given the different needs of marketers, differences in traffic quality across campaigns and the noisy nature of internet traffic, we propose the use of equality testing of two proportions to highlight flags which are important in certain situations. We present measurements of real-world traffic using these flags.
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Acknowledgements
R.W. thanks Codewise for the possibility to work towards his Ph.D. This work was partially supported by the Polish Ministry of Science and Higher Education under subvention funds for the AGH University of Science and Technology.
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Wiatr, R., Lyutenko, V., Demczuk, M., Słota, R., Kitowski, J. (2020). Click-Fraud Detection for Online Advertising. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2019. Lecture Notes in Computer Science(), vol 12043. Springer, Cham. https://doi.org/10.1007/978-3-030-43229-4_23
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DOI: https://doi.org/10.1007/978-3-030-43229-4_23
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