Review on e-Learning Environment Development and context aware recommendation systems using Deep Learning
Gaurav Srivastav, Shri Kant · 2019
Internet has open platforms for various domains to interact with each other. e-leaning is a domain which consistently getting attention because of “Learn any-time, anywhere” approach. Since, the start of e-learning environment development phase semantic web base ontology is used for describing and making relation between Learning Objects (LO's). Since contents are increasing every day, on this point ontologies are lagging to recommend. Development of recommendation using deep learning techniques are producing comparatively better results. Deep learning is now been used for classification, predictions, recommendations. It is also used in detection and segmentation techniques as well. This paper presents discussion various categories of recommendation systems. Then a comparative study is on deep learning-based recommendation systems. Major challenge that an e-learning environment is facing is because of “Cold-Start” and “Sparsity” in content based (CB) & collaborative Filter (CF) based recommendation systems. How to reduce Cold-Start and Sparsity is tried to find out in this paper.