Design of a recommendation system based on collaborative filtering and machine learning considering personal needs of the user

Design of a recommendation system based on collaborative filtering and machine learning considering personal needs of the user

The paper reports a study into recommendation algorithms and determination of their advantages and disadvantages. The method for developing recommendations based on collaborative filtering such as Content-Based Filtering (CBF), Collaborative Filtering (CF), and hybrid methods of Machine Learning (ML...

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Bibliographic Details
Main Authors: Vasyl Lytvyn, Victoria Vysotska, Viktor Shatskykh, Ihor Kohut, Oksana Petruchenko, Lyudmyla Dzyubyk, Vitaliy Bobrivetc, Valentyna Panasyuk, Svitlana Sachenko, Myroslav Komar
Format: Article
Language:English
Published: PC Technology Center 2019-08-01
Series:Eastern-European Journal of Enterprise Technologies
Subjects:
commercial content
personalization
machine learning
seo technology
search metrics
e-commerce
nlp
Online Access:http://journals.uran.ua/eejet/article/view/175507

Internet

http://journals.uran.ua/eejet/article/view/175507

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