Analysis of methods, models and algorithms of personalization for the recommender systems development
DOI:
https://doi.org/10.15587/2313-8416.2018.152949Keywords:
personalization, methods, models, algorithms and taxonomy of knowledge for recommender systemsAbstract
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
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