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Optimization of click-through rate prediction in the Yandex search engine

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Abstract

The problem of the estimation of the click-through rate on advertisements that are placed on a search-engine results page is discussed. The proposed methods improved the prediction quality (both in terms of likelihood metrics and the principle parameters of the engine). The cases of advertisement displays are considered when the history of an ad is rather short (i.e., advertisements that are considered to be new). The proposed prediction formula takes the dispersion and high risk of displaying a new advertisement into account.

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Authors and Affiliations

  1. Higher School of Economics, Myasnitskaya ul. 20, Moscow, Russia

    K. E. Bauman, A. N. Kornetova, V. A. Topinskii & D. A. Khakimova

Authors
  1. K. E. Bauman
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  2. A. N. Kornetova
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  3. V. A. Topinskii
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  4. D. A. Khakimova
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Corresponding author

Correspondence to K. E. Bauman.

Additional information

Original Russian Text © K.E. Bauman, A.N. Kornetova, V.A. Topinskii, D.A. Khakimova, 2013, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2, 2013, No. 4, pp. 1–8.

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Bauman, K.E., Kornetova, A.N., Topinskii, V.A. et al. Optimization of click-through rate prediction in the Yandex search engine. Autom. Doc. Math. Linguist. 47, 52–58 (2013). https://doi.org/10.3103/S0005105513020040

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  • DOI: https://doi.org/10.3103/S0005105513020040

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