Comparison of Selected Algorithms in Movie Recommender System
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Comparison of Selected Algorithms in Movie Recommender System
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Comparison of Selected Algorithms in Movie Recommender System
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Applied Sciences
ISSN
2076-3417
e-ISSN
2076-3417
Svazek periodika
—
Číslo periodika v rámci svazku
17
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
28
Strana od-do
—
Kód UT WoS článku
001569546700001
EID výsledku v databázi Scopus
2-s2.0-105015581459