Intelligent Recommendation System for Course Selection in Smart Education

Being an essential component of smart education, we propose a novel recommendationsystem for course selection in the specialty of information management inChinese Universities.To implement this system, we firstly collect the course enrollment data-set for specific group of students. The sparse linear method (SLIM) is introduced in our framework to generate the top-N recommendations of courses appropriate to the students. Meanwhile, aL(o) regularization term isexploited as the optimization strategywhich is established on the observation of the course items in the current recommendation system. The comparison experiments betweenstate-of-the-art methods and our approachare conducted to evaluate the performance of our method. Experimental results of different topics and number of courses both show that our proposed method outperforms state-of-the-art methods both in accuracy and efficiency. Copyright (C) 2018 Elsevier Ltd. All rights reserved.