ADVERTISING BIDDING OPTIMIZATION BY TARGETING BASED ON SELF-LEARNING DATABASE
OPTYMALIZACJA OFERT REKLAMOWYCH POPRZEZ UKIERUNKOWANIE W OPARCIU O SAMOUCZĄCĄ SIĘ BAZĘ DANYCH
Kvуetnyy R. Bunyak Y. Sofina O. Kaduk O. Mamyrbayev O. Baklaiev V. Yeraliyeva B.
2023Politechnika Lubelska
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Srodowiska
2023#13Issue 466 - 72 pp.
The method of targeting advertising on Internet sites based on a structured self-learning database is considered. The database accumulates data on previously accepted requests to display ads from a closed auction, data on participation in the auction and the results of displaying ads – the presence of a click and product installation. The base is structured by streams with features – site, place, price. Each such structural stream has statistical properties that are much simpler compared to the general ad impression stream, which makes it possible to predict the effectiveness of advertising. The selection of bidding requests only promising in terms of the result allows to reduce the cost of displaying advertising.
advertising bidding , click prediction , targeted advertising , targeting
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Vinnytsia National Technical University, Vinnytsia, Ukraine
Spilna Sprava Company, Vinnytsya, Ukraine
Institute of Information and Computational Technologies of the Kazakh National Technical University named after K. I. Satbayev, Almaty, Kazakhstan
Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
M. Kh. Dulaty Taraz Regional University, Taraz, Kazakhstan
Vinnytsia National Technical University
Spilna Sprava Company
Institute of Information and Computational Technologies of the Kazakh National Technical University named after K. I. Satbayev
Taras Shevchenko National University of Kyiv
M. Kh. Dulaty Taraz Regional University
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