NEW RECOMMENDER SYSTEM USING NAIVE BAYES FOR E-LEARNING

Year 2016, Volume: 5 , 309 - 312, 01.09.2016

Mehmet Ozcan Tansu Temel

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. 

Keywords

Naive bayes, data preprocessing, e-learning, recommendation systems

References

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