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Semantics in Educational Recommender Systems

Vallamkondu, Manasa
Master thesis
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URI
http://hdl.handle.net/11250/2615828
Date
2016
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  • Institutt for datateknologi og informatikk [3873]
Abstract
Recommender systems are information filtering systems that rank items according

to user interests and preferences. They are widely used on online shopping sites

like Amazon and Netflix, but have also become increasingly popular in educational

contexts and on e-learning platforms. Many recent recommender systems employ

various semantic techniques to increase the accuracy of the systems or enrich the

user experience in general.

The purpose of this study is to investigate the requirement of Semantics in Educational

Recommender Systems and to survey the existing recommender systems for education and e-learning. This study analyzes how recommender systems can be applied to current e-learning systems to guide learners in a personalized way by including e-learning scenarios and a framework providing the classication of the recommender system based on the underlying technology and educational purpose.

Keywords: Semantic recommendation, Educational Recommender Systems,

Semantics in Educational Recommender Systems, Semantics Recommender Systems,

Emotions, Technology enhanced learning, E-learning services.
Publisher
NTNU

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