New Recommender System Using Naive Bayes for E-Learning

Research Highlights in Education and Science 2016

Editors: Wenxia Wu, Selahattin Alan, Mustafa Tevfik Hebebci


Research Highlights in Education and Science 2016

3753

New Recommender System Using Naive Bayes for E-Learning

Chapter Authors: Mehmet Özcan, Furkan Göz, Tansu Temel

Pages: 62-68

Abstract: Coming into prominence at the present time, e-learning is a great opportunity for learners. It provides tremendous assets most valuable of which is distance free learning. Besides, there is a great deal of e-learning resources on the web that causes information overload. Accordingly, it turns into a requisite that you ask for recommendation so as to find the resource you surely need. There are readily available recommendation services arranged for that purpose. Such systems have various rating systems; furthermore, users tend to rate the materials in different manners. Our goal with this paper is to generate confidential referrals thanks to Naive Bayesian algorithm for e-learning materials rated multifariously by learners. We also researched the effects of several data preprocessing techniques on achieving this goal.

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