Hybrid Recommender System for E-Learning Platforms

Internet use has steadily increased over the past 25 years. Numerous online services are improving and simplifying life for people. E-learning is one of these services, which makes the learning process simpler. In this work, a recommendation system will be presented that will assist online course providers in automating course suggestion. By finding patterns in courses based on some attributes like field of interest, skill set, educational qualification, course content, etc. of an individual and courses, this recommendation system is built using hybrid machine learning recommendation techniques, i.e., combination of Collaborative (item based) and content-based recommendation and KNN classifiers. Lastly, the recommendations are pooled from the two blocks of recommended courses (which were discovered using a collaborative technique), similar courses (which is found using content-based finding).