Volume 11, Number 6

Cluster Based Association Rule Mining for Courses Recommendation System


Wael Ahmad AlZoubi, Balqa Applied University, Jordan


A course recommender system has a great importance in expecting the selection of courses by students in an university, especially for new students who can't easily select the proper elective courses offered for a specific semester. The computer science department in Ajloun University College at Balqa Applied University (BAU) will be taken as a case study. In this paper, an efficient cluster based rule mining algorithm will be used on a course database to describe a courses recommendation system that assist students to choose elective courses based on students already studied these courses or some of them.


Collaborative Filtering, Cluster, Association Rules, Recommendation System