NEW RECOMMENDER SYSTEM USING NAIVE BAYES FOR E-LEARNING

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.