Recommendation System for Cloud Resources to Impaired Vision Students through Collaborative Filtering
Personalized E-learning based on recommended system is recognized as one of the most favourable research field to advance education and teaching to the next level. Impaired vision students can able to access the online resources. But it primarily deals with inability in learning resources for impaired vision students using cloud resource or materials. The proposed personalized recommendation system uses the collaborative filtering techniques for improving a personalized E-learning system for impaired vision people easy accessing of their cloud materials. Using impaired vision learner profile, the system proposes a personalize learning activity for cloud resource platform provides the related contents and resources to improve the education skills. Accessibility of websites for impaired vision students are possible with help of screen reading software, i.e. JAWS. The proposed work extracts user rating from various cloud resources such as khan Academy, YouTube etc. and suggests the users whether the course is suitable or not.