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Chapitre D'ouvrage Année : 2017

Regression tree for bandits models in A/B testing

Résumé

In the context of Web A/B testing, dynamic assignment of traffic aims to promote the best variation (A or B) as quickly as possible. However, dynamic assignment is difficult to use when the difference between A and B affects the visitor differently according to his / her personal characteristics and his / her history (number of visits, navigation on the website ...). In this paper, we propose a dynamic assignment strategy based on a visitor segmentation determined automatically from the visitors navigation and characteristics.
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Dates et versions

hal-02572444 , version 1 (13-05-2020)

Identifiants

  • HAL Id : hal-02572444 , version 1

Citer

Emmanuelle Claeys, Pierre Gancarski, Myriam Maumy-Bertrand, Hubert Wassner. Regression tree for bandits models in A/B testing. The Sixteenth International Symposium on Intelligent Data Analysis (IDA 2017), 2017. ⟨hal-02572444⟩
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