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  • The Application of Deep Learning Techniques to the Task of Probabilistic User Identification in the Context of an Advertising Platform

The Application of Deep Learning Techniques to the Task of Probabilistic User Identification in the Context of an Advertising Platform

Student: Anton Zolotarev

Supervisor: Alexey Masyutin

Faculty: Faculty of Computer Science

Educational Programme: Financial Technology and Data Analysis (Master)

Year of Graduation: 2024

To enhance user privacy, in recent years most web browsers have taken steps to block or restrict third-party cookies. This trend endangers the ability of advertisement platforms to provide quality advertisement targeting as it reduces the completeness of the profile collected about the user. In order to minimize the damage caused by these restrictions, advertising platforms are trying different solutions, including probabilistic user identification based on first-party cookies, matching them together to form a synthetic third-party cookie. In this paper, there was implemented a method for recovering third-party cookies by matching together a set of first-party cookies via browser parameters, device parameters, and user's browsing history based on big data and machine learning techniques. As a result, a solution was obtained that allows to link user's history from several sites without direct use of third-party cookies that lose relevance.

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