Object's details: The intellectual system of movies recommendations based on the collaborative filtering

Provider:Akademicka Platforma Czasopism

Description

Title:
The intellectual system of movies recommendations based on the collaborative filtering
Creator:
Sitkar, Stepan;
Voitovych, Oksana;
Horbatiuk, Roman;
Sitkar, Taras;
Shrol, Tetiana;
Poliukhovych, Nataliia;
Grygus, Igor;
Zukow, Walery
Description:
The investigation deals with designing and developing of intellectual system of movies recommendations  based on the collaborative filtering using the Python software environment. In particular, the approaches (Content-based approach, Collaborative filtering, Hybrid models) in recommendatory system construction with the help of neural networks have been analyzed. It has been established that it is difficult to implement and learn the Content-based approach and it strongly depends on the subject area. Collaborative filtering is more simple in implementation, training, it is universal, but it has a flaw in the form of a «cold-start». Accordingly, the collaborative filtering has been chosen for the design and development of the intellectual system of movies recommendations. While designing a system of recommendations based on collaborative filtering, the Naive Recommendations, Recommendations based on average ratings of similar users, Recommendations based on average user ratings and similarity matrix have been described; their algorithm and their implementation using the Python software environment have been demonstrated. As a result the intellectual system of recommendations has been realized and it can offer a movie to the user according to his/her preferences.
Object availability:
free access
Rights: http://creativecommons.org/licenses/by-nc-sa/4.0 ;
Prawa autorskie (c) 2022 Stepan Sitkar, Oksana Voitovych, Roman Horbatiuk, Taras Sitkar, Tetiana Shrol, Nataliia Poliukhovych, Igor Grygus, Walery Zukow
Date:
2022.03.16
Type:
info:eu-repo/semantics/article;
info:eu-repo/semantics/publishedVersion
Language:
English
Source:
Journal of Education, Health and Sport; Vol. 12 No. 3 (2022); 115-127;
Journal of Education, Health and Sport; Tom 12 Nr 3 (2022); 115-127;
2391-8306
Format:
application/pdf
Publisher:
Nicolaus Copernicus University, Toruń, Poland
Relation: https://apcz.umk.pl/JEHS/article/view/37709/31822
Subject:
Collaborating filtering;
recommendation system;
neural network;
naive recommendation;
recommendations based on average ratings of similar users;
recommendations based on average user ratings and similarity matrix
Identifier: https://apcz.umk.pl/JEHS/article/view/37709
Data provider:
Akademicka Platforma Czasopism

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