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Mini Review Open Access June 27, 2022

Open-Source Datasets for Recommender Systems Analysis

Raja Marappan 1,*
1
School of Computing, SASTRA Deemed University, Thanjavur, India
Publihed in: Universal Journal of Physics Research (Volume 1, Issue 2, 2022)
Page(s): 49-51
DOI: 10.31586/ijmebac.2022.350
Received
May 07, 2022
Revised
June 17, 2022
Accepted
June 25, 2022
Published
June 27, 2022
Keywords
Recommender Systems; Traditional Datasets; Nontraditional Datasets; Systems Analysis
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). Open-Source Datasets for Recommender Systems Analysis. Universal Journal of Physics Research, 1(2), 49-51. https://doi.org/10.31586/ijmebac.2022.350
ACS Style
Marappan, R. Open-Source Datasets for Recommender Systems Analysis. Universal Journal of Physics Research 2022 1(2), 49-51. https://doi.org/10.31586/ijmebac.2022.350
Chicago/Turabian Style
Marappan, Raja. 2022. "Open-Source Datasets for Recommender Systems Analysis". Universal Journal of Physics Research 1, no. 2: 49-51. https://doi.org/10.31586/ijmebac.2022.350
AMA Style
Marappan R. Open-Source Datasets for Recommender Systems Analysis. Universal Journal of Physics Research. 2022; 1(2):49-51. https://doi.org/10.31586/ijmebac.2022.350 
@Article{ujpr350,
AUTHOR = {Marappan, Raja},
TITLE = {Open-Source Datasets for Recommender Systems Analysis},
JOURNAL = {Universal Journal of Physics Research},
VOLUME = {1},
YEAR = {2022},
NUMBER = {2},
PAGES = {49-51},
URL = {https://www.scipublications.com/journal/index.php/IJMEBAC/article/view/350},
ISSN = {2834-5479},
DOI = {10.31586/ijmebac.2022.350},
ABSTRACT = {There are different traditional and nontraditional datasets available to investigate the performance of recommender systems. This article focuses on the different datasets required for the investigation of recommender systems.},
}
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%J Universal Journal of Physics Research

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%T Open-Source Datasets for Recommender Systems Analysis
%M doi:10.31586/ijmebac.2022.350
%U https://www.scipublications.com/journal/index.php/IJMEBAC/article/view/350

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UR  - https://www.scipublications.com/journal/index.php/IJMEBAC/article/view/350
AB  - There are different traditional and nontraditional datasets available to investigate the performance of recommender systems. This article focuses on the different datasets required for the investigation of recommender systems.
DO  - Open-Source Datasets for Recommender Systems Analysis
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