Profile Based Course Recommendation System Using Association Rule Mining and Collaborative Filtering

Online Education is a great blessing of modern technology. In the present world, online education has become the most popular choice of students in developing new skills. Even many of the universities in the world have offered their higher studies program through the online education system where any student from any place of the world can achieve their higher studies via the internet. Internet is getting loaded with new educational resources every day. And in this vast sea of resources students should know which are the skills needed to learn to build a successful career. Students should acquire knowledge that adds value to their life and society. The main purpose of this paper is to present a structured framework of an intellectual recommendation system for self-learners so that they can get right direction and a personalized learning road-map through recommendations. In recent years, Recommendation system has developed rapidly and used widely. In online educational system recommendation system can be used to provide educational resources to students that matches their interests of learning. Personalized recommendation will be provided to the students through mining data. Student’s activity will be recorded and stored in profiles. We have an intelligent support system to support our learners to select their courses as per their educational qualifications. We mainly developed the Recommendation System (RS) with a hybrid approach using Association Rule Mining and User-based Collaborative Filtering. Traditional Recommendation algorithms can fulfill students’ needs to a certain extent thus we chose to approach hybrid methods. Hybrid methods can identify different student’s unique interest in learning materials more effectively resulting in more personalized recommendations to the students. In this always evolving world, if anyone want to progress towards more fulfilling career and achieve their aspirations self-learning is essential.