ANALYSIS OF CONTENT RECOMMENDATION METHODS IN INFORMATION SERVICES
Oleksandr Necheporuk
Sumy State University (Ukraine)
https://orcid.org/0000-0002-9905-031X
Svitlana Vashchenko
Sumy State University (Ukraine)
Nataliia Fedotova
n.fedotova@cs.sumdu.edu.uaSumy State University (Ukraine)
https://orcid.org/0000-0001-9304-1693
Iryna Baranova
Sumy State University (Ukraine)
https://orcid.org/0000-0002-3767-8099
Yaroslava Dehtiarenko
Lublin University of Technology (Poland)
Abstract
The object of the research is the process of selecting a content recommendation method in information services. The study's relevance stems from the rapid development of informational and entertainment resources and the increasing volume of data they operate on, thus prompting the utilisation of recommendation systems to maintain user engagement. Considering the different types of content, it is necessary to address the problem of data filtration based on their characteristics and user preferences. To solve this task, we analysed content-based and collaborative filtering methods using various techniques (model-based, memory-based, and hybrid collaborative filtering techniques), knowledge-based filtering, and hybrid filtering methods. Considering each method's advantages and disadvantages, we chose a hybrid method using model-based collaborative filtering and content-based filtering for the future development of our universal recommendation system.
Keywords:
content-based recommender system, collaborative recommender system, hybrid recommender systemReferences
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Authors
Svitlana VashchenkoSumy State University Ukraine
Authors
Nataliia Fedotovan.fedotova@cs.sumdu.edu.ua
Sumy State University Ukraine
https://orcid.org/0000-0001-9304-1693
Authors
Yaroslava DehtiarenkoLublin University of Technology Poland
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