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International Journal of Advanced Computer Science and Applications(ijacsa), Volume 9 Issue 9, 2018.
Abstract: Due to the huge amounts of online learning materials, e-learning environments are becoming very popular as means of delivering lectures. One of the most common e-learning challenges is how to recommend quality learning materials to the students. Personalized e-learning recommender systems help to reduce information overload, which tailor learning material to meet individual student’s learning needs. This research focuses on using various recommendation and data mining techniques for personalized learning in e-learning environment.
Hayder Murad and Linda Yang, “Personalized E-Learning Recommender System using Multimedia Data” International Journal of Advanced Computer Science and Applications(ijacsa), 9(9), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090971
@article{Murad2018,
title = {Personalized E-Learning Recommender System using Multimedia Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090971},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090971},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {9},
author = {Hayder Murad and Linda Yang}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.