Automated Online Course Recommendation System using Collaborative Filtering

Abstract

In the digital world of online information huge amounts of Massive Open Online Courses (MOOCs) are available of different category and domain. Multiple online courses are available on different platform finding appropriate course from this massive available course is difficult for students. Recommender system plays vital role in finding appropriate courses to students. Managing massive amount of information and identifying individual users' choice and behavior has become tedious task nowadays, so the aim of recommender system is to suggest relevant course to student based on user behavior and similarity with another course. Several recommender system techniques are being implemented like content based, collaborative, Knowledge based. This paper aims to build a hybrid approach using collaborative filtering with content base filtering. This system recommendation is based on course description and ratings. Experiments were conducted on real datasets to get the overall performance of proposed system.