TY  - JOUR
TT  - NEW RECOMMENDER SYSTEM USING NAIVE BAYES FOR E-LEARNING
AU  - Ozcan, Mehmet
AU  - Temel, Tansu
PY  - 2016
DA  - September
JF  - The Eurasia Proceedings of Educational and Social Sciences
JO  - EPESS
PB  - ISRES Publishing
WT  - DergiPark
SN  - 2587-1730
SP  - 309
EP  - 312
VL  - 5
KW  - Naive bayes
KW  - data preprocessing
KW  - e-learning
KW  - recommendation systems
N2  - Cominginto prominence at the present time, e-learning is a great opportunity forlearners. It provides tremendous assets most valuable of which is distance freelearning. Besides, there is a great deal of e-learning resources on the webthat causes information overload. Accordingly, it turns into a requisite thatyou ask for recommendation so as to find the resource you surely need. Thereare readily available recommendation services arranged for that purpose. Suchsystems have various rating systems; furthermore users tend to rate thematerials in different manners. Our goal with this paper is to generateconfidential referrals thanks to Naive Bayesian algorithm for e-learningmaterials rated multifariously by learners. We also researched the effects of severaldata preprocessing techniques on achieving this goal. 
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UR  - https://dergipark.org.tr/en/pub/epess/issue//366810
L1  - https://dergipark.org.tr/en/download/article-file/384198
ER  -