Comparison of Selected Algorithms in Movie Recommender System

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F25%3AA2603C7Q" target="_blank" >RIV/61988987:17310/25:A2603C7Q - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2076-3417/15/17/9518" target="_blank" >https://www.mdpi.com/2076-3417/15/17/9518</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app15179518" target="_blank" >10.3390/app15179518</a>

Result language
angličtina
Original language name
Comparison of Selected Algorithms in Movie Recommender System
Original language description
Recommender systems are currently very popular, and their main goal is to propose relevant content to users based on various parameters. The main goal of this paper is to create a comprehensive comparison of selected algorithms in movie recommender systems. The recommender system works with the MovieLens database. The main output of the proposed comparison is finding the best algorithm for selecting movies that are the most relevant to user preferences. The paper contains experimental verification of the performance of the proposed algorithms, with an emphasis on their evaluation based on metrics such as Precision, Recall and F1 score. The goal of the evaluation is to assess how well each algorithm performs in generating accurate and relevant recommendations. The testing process includes analysis of the results achieved on the test set of users.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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