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Martín Blanco, Miguel Carlos, Jiménez Martín, Antonio ORCID: https://orcid.org/0000-0002-4947-8430 and Mateos Caballero, Alfonso
ORCID: https://orcid.org/0000-0003-4764-6047
(2019).
The multi-armed bandit problem under delayed rewards conditions in digital campaign management.
In: "6th International Conference on Control, Decision and Information Technologies (CoDIT’19)", 23-26 Abr 2019, París, Francia. pp. 952-959.
https://doi.org/10.1109/CoDIT.2019.8820666.
Title: | The multi-armed bandit problem under delayed rewards conditions in digital campaign management |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | 6th International Conference on Control, Decision and Information Technologies (CoDIT’19) |
Event Dates: | 23-26 Abr 2019 |
Event Location: | París, Francia |
Title of Book: | Proceedings of the 6th International Conference on Control, Decision and Information Technologies (CoDIT’19) |
Date: | September 2019 |
Subjects: | |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Inteligencia Artificial |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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In this paper, we account for a digital marketing content recommendation system, called campaign management, used by marketers to create specific digital content that can be issued or configured for viewing by certain population segments according to a series of business variables, user profile or behavior. We analyze the most representative allocation strategies to deal with the multi-armed bandit problem in a context with delayed rewards by means of a numerical study based on a discrete event simulation. Both batch mode and online update architectures are considered for feedback from the different contents displayed to users.
Item ID: | 64629 |
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DC Identifier: | https://oa.upm.es/64629/ |
OAI Identifier: | oai:oa.upm.es:64629 |
DOI: | 10.1109/CoDIT.2019.8820666 |
Official URL: | https://ieeexplore.ieee.org/abstract/document/8820... |
Deposited by: | Memoria Investigacion |
Deposited on: | 15 Oct 2020 07:14 |
Last Modified: | 15 Oct 2020 07:14 |