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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Personalized E-Learning Recommender System using Multimedia Data

Author 1: Hayder Murad Author 2: Linda Yang
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 9 · Published 2018 · Cited by 17

DOI: https://doi.org/10.14569/IJACSA.2018.090971

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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.

Keywords

E-Learning recommender system data mining

How to Cite this Article

Murad, H., & Yang, L. (2018). Personalized E-Learning Recommender System using Multimedia Data. International Journal of Advanced Computer Science and Applications, 9(9). https://doi.org/10.14569/IJACSA.2018.090971

Murad, Hayder, and Linda Yang. "Personalized E-Learning Recommender System using Multimedia Data." International Journal of Advanced Computer Science and Applications, vol. 9, no. 9, 2018, https://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},
  volume    = {9},
  number    = {9},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Hayder Murad and Linda Yang},
  doi       = {10.14569/IJACSA.2018.090971},
  url       = {https://doi.org/10.14569/IJACSA.2018.090971}
}

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