Machine learning driven course recommendation system
Sara Lazarevic, Tamara Zuvela, Sofija Djordjevic, Srdjan Sladojević, Marko Arsenović · 2022
This paper presents a machine learning-driven course recommendation system based on similarities between courses. The proposed system employs various data mining techniques to mentioned similarities between courses. Based on the experimental phase of this paper, Cosine metrics proved the best to calculate these parameters. The method proposed in this paper relies on rankings based on areas of study. These techniques allowed us to create an algorithm that, based on input, returns courses that satisfy various conditions. The results satisfy the demands of finding similar courses presented through cross-platform application to the students who will use it to improve their education.