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Mini Review Open Access June 21, 2022

Recommender System for Movielens Datasets using an Item-based Collaborative Filtering in Python

Raja Marappan 1,*
1
School of Computing, SASTRA Deemed University, Thanjavur, India
Publihed in: Current Research in Public Health (Volume 1, Issue 1, 2022)
Page(s): 42-43
DOI: 10.31586/ijmebac.2022.340
Received
May 12, 2022
Revised
June 11, 2022
Accepted
June 19, 2022
Published
June 21, 2022
Keywords
Movie Recommendation; Recommendation System; Movies Preferences; Collaborative Filtering
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2022. Published by Scientific Publications
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Cite This Article

APA Style
Marappan, R. (2022). Recommender System for Movielens Datasets using an Item-based Collaborative Filtering in Python. Current Research in Public Health, 1(1), 42-43. https://doi.org/10.31586/ijmebac.2022.340
ACS Style
Marappan, R. Recommender System for Movielens Datasets using an Item-based Collaborative Filtering in Python. Current Research in Public Health 2022 1(1), 42-43. https://doi.org/10.31586/ijmebac.2022.340
Chicago/Turabian Style
Marappan, Raja. 2022. "Recommender System for Movielens Datasets using an Item-based Collaborative Filtering in Python". Current Research in Public Health 1, no. 1: 42-43. https://doi.org/10.31586/ijmebac.2022.340
AMA Style
Marappan R. Recommender System for Movielens Datasets using an Item-based Collaborative Filtering in Python. Current Research in Public Health. 2022; 1(1):42-43. https://doi.org/10.31586/ijmebac.2022.340 
@Article{crph340,
AUTHOR = {Marappan, Raja},
TITLE = {Recommender System for Movielens Datasets using an Item-based Collaborative Filtering in Python},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2022},
NUMBER = {1},
PAGES = {42-43},
URL = {https://www.scipublications.com/journal/index.php/IJMEBAC/article/view/340},
ISSN = {2831-5162},
DOI = {10.31586/ijmebac.2022.340},
ABSTRACT = {Everyone likes movies irrespective of color, gender, age, location, and race. The most important thing is how the users are getting our unique combinations of choices concerning the preferences of the movies. This article focuses on the creation of a movie recommendation system using item-based collaborative filtering.},
}
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%U https://www.scipublications.com/journal/index.php/IJMEBAC/article/view/340

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AB  - Everyone likes movies irrespective of color, gender, age, location, and race. The most important thing is how the users are getting our unique combinations of choices concerning the preferences of the movies. This article focuses on the creation of a movie recommendation system using item-based collaborative filtering.
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