Modern Probabilistic Model: Filtering Massive Data in E-learning

  • Hachem Harouni Alaoui Mathematics & Computer Department, Faculty of Sciences, Moulay Ismail University, Meknes, Morocco
  • Elkaber Hachem Mathematics & Computer Department, Faculty of Sciences, Moulay Ismail University, Meknes, Morocco
  • Cherif Ziti Mathematics & Computer Department, Faculty of Sciences, Moulay Ismail University, Meknes, Morocco
Keywords: E-learning platforms, IT tools, LDA, machine learning

Abstract

So muchinformation keeps on being digitized and stored in several forms, web pages, scientific articles, books, etc. so the mission of discovering information has become more and more challenging. The requirement for new IT devices to retrieve and arrange these vastamounts of informationaregrowing step by step. Furthermore, platforms of e-learning are developing to meet the intended needsof students.
The aim of this article is to utilize machine learning to determine the appropriate actions that support the learning procedure and the Latent Dirichlet Allocation (LDA) so as to find the topics contained in the connections proposed in a learning session. Ourpurpose is also to introduce a course which moves toward the student's attempts and which reduces the unimportant recommendations (Which aren’t proper to the need of the student grown-up) through the modeling algorithms of the subjects.

Published
2021-01-13
How to Cite
Hachem Harouni Alaoui, Elkaber Hachem, & Cherif Ziti. (2021). Modern Probabilistic Model: Filtering Massive Data in E-learning. Iraqi Journal of Science, 52-58. https://doi.org/10.24996/ijs.2021.SI.1.8

Most read articles by the same author(s)