Abstract
In this paper we present an algorithm that identifies fraud in online advertising systems such as CPC (Cost Per Click also called PPC Pay-Per-Click). This model used in online advertising is particularly sensitive because it can be exploited by making invalid clicks on an advertisement. This results in additional costs for the advertiser, reduced possibility of reaching the most interested viewers and fraudulent results of an advertising campaign. The dynamically modified BoW (Bag-Of-Words) algorithm presented in the article allows us to identify repetitive clicks made by dishonest publishers or by automatic software, i.e. bots. The algorithm uses data obtained directly on an advertiser’s website. The paper also presents the results of an experimental research confirming effectiveness of the proposed methods.
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Gabryel, M., Przybyszewski, K. (2019). The Dynamically Modified BoW Algorithm Used in Assessing Clicks in Online Ads. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_32
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