Online advertising, as a vast market, has gained significant attention in various platforms
ranging from search engines, third-party websites, social media, and mobile apps. The …

It is widely recognised that the ability of e-commerce businesses to predict conversion
probability, ie, acceptance probability, is critically important in today's business environment …

We address the problem of self-supervised learning on discrete event sequences generated
by real-world users. Self-supervised learning incorporates complex information from the raw …

With the availability of big customer data and advances in machine learning techniques, the
prediction of customer behavior at the session-level has attracted considerable attention …

We tackle the challenge of in-session attribution for on-site search engines in eCommerce.
We phrase the problem as a causal counterfactual inference, and contrast the approach with …

Abstract Die Identifizierung von Sessions zum Verständnis des Benutzerverhaltens ist ein
gängiges Forschungsgebiet des Web Usage Mining. Der Begriff wird verwendet, um die …

In this paper we consider a challenging problem of learning discriminative vector
representations for event sequences generated by real-world users. Vector representations …

Анотація У зв'язку зі швидким розвитком Інтернет-торгівлі та посилення конкуренції на
роздрібному ринку України компанії змушені шукати нові шляхи для росту власного …

When a business sells to another business (B2B), the buying business is represented by a
group of individuals, termed account, who collectively decide whether to buy. The seller …

Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market A Thesis
submitted to the Faculty of the Graduat Page 1 Essays on Consumer Heterogeneity and …