Аналіз методів, моделей та алгоритмів персоналізації для розроблення рекомендаційних систем
DOI:
https://doi.org/10.15587/2313-8416.2018.152949Słowa kluczowe:
персоналізація, методи, моделі, алгоритми та таксономія знань для рекомендаційних системAbstrakt
В статті досліджуються методи, моделі та алгоритми персоналізації в цифровому середовищі. Наведена загальна характеристика типів рекомендаційних систем, їх методи, моделі та алгоритми, переваги та недоліки застосування. В роботі запропоновано застосування таксономії знань для створення інтелектуального додатку персоналізації для підтримки прийняття маркетингових рішень для підприємств у цифровому середовищі. Виділено додаткові джерела даних для створення рекомендацій
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