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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Machine Learning Technology Overview In Terms Of Digital Marketing And Personalization

Authors:

Anna Nikolajeva, Artis Teilans

Published in:

 

 

(2021). ECMS 2021, 35th Proceedings
Edited by: Khalid Al-Begain, Mauro Iacono, Lelio Campanile, Andrzej Bargiela, European Council for Modelling and Simulation.

 

DOI: http://doi.org/10.7148/2021

ISSN: 2522-2422 (ONLINE)

ISSN: 2522-2414 (PRINT)

ISSN: 2522-2430 (CD-ROM)

 

ISBN: 978-3-937436-72-2
ISBN: 978-3-937436-73-9(CD)

 

Communications of the ECMS , Volume 35, Issue 1, June 2021,

United Kingdom

 

Citation format:

Anna Nikolajeva, Artis Teilans (2021). Machine Learning Technology Overview In Terms Of Digital Marketing And Personalization, ECMS 2021 Proceedings Edited By: Khalid Al-Begain, Mauro Iacono, Lelio Campanile, Andrzej Bargiela European Council for Modeling and Simulation. doi: 10.7148/2021-0125

DOI:

https://doi.org/10.7148/2021-0125

Abstract:

The research is dedicated to artificial intelligence technology usage in digital marketing personalization. The doctoral theses will aim to create a machine learning algorithm that will increase sales by personalized marketing in electronic commerce website. Machine learning algorithms can be used to find the unobservable probability density function in density estimation problems. Learning algorithms learn on their own based on previous experience and generate their sequences of learning experiences, to acquire new skills through self-guided exploration and social interaction with humans. An entirely personalized advertising experience can be a reality in the nearby future using learning algorithms with training data and new behaviour patterns appearance using unsupervised learning algorithms. Artificial intelligence technology will create website specific adverts in all sales funnels individually.

Full text: