Analysis of methods, models and algorithms of personalization for the recommender systems development

Authors

  • Yuliia Kotliarova Educational and Scientific Institute "Institute Information Technologies in Economics" Kyiv National Economic University named after Vadym Hetman" Lvivska sq., 14, Kyiv, Ukraine, 04053, Ukraine https://orcid.org/0000-0001-5734-9252

DOI:

https://doi.org/10.15587/2313-8416.2018.152949

Keywords:

personalization, methods, models, algorithms and taxonomy of knowledge for recommender systems

Abstract

In the article the methods, models and algorithms of personalization in the digital environment are investigated. The general characteristic of types of recommender systems, their methods, models and algorithms, advantages and disadvantages of application are given. The paper proposes to use taxonomy of knowledge for creating an intelligent personalization application to support the adoption of marketing solutions for enterprises in the digital environment. Additional data sources have been allocated to create recommendations

Author Biography

Yuliia Kotliarova, Educational and Scientific Institute "Institute Information Technologies in Economics" Kyiv National Economic University named after Vadym Hetman" Lvivska sq., 14, Kyiv, Ukraine, 04053

Postgraduate Student, Assistant

Department of Information Systems in Economics

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Published

2018-11-27

Issue

Section

Economics