Performance Comparison of Machine Learning Algorithms in Movie Recommender Systems

Pireci Sejdiu, Nora and Ristevski, Blagoj and Jolevski, Ilija (2022) Performance Comparison of Machine Learning Algorithms in Movie Recommender Systems. In: 57th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST) 2022, 16-18 June 2022, Ohrid, Macedonia.

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We are all aware that the use of technology in every domain of life produces an enormous amount of information by overloading the amount of data on the Internet. To make data
access easier, recommendation systems have been shown to be
more efficient, especially performance enhancement has been
significantly increased with the integration and use of machine learning algorithms. This paper compares the performance of three machine learning algorithms: Naïve Bayes, neural networks and logistic regression when applied on a movie recommender system. The movie recommender system is implemented in Python programming language using the MovieLens dataset.

Item Type: Conference or Workshop Item (Paper)
Subjects: Scientific Fields (Frascati) > Natural sciences > Computer and information sciences
Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering
Divisions: Faculty of Information and Communication Technologies
Depositing User: Prof. d-r. Blagoj Ristevski
Date Deposited: 24 Aug 2022 15:23
Last Modified: 24 Aug 2022 15:23

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