Business Intelligence

A Comparative Study of Association Rule Algorithms for Course Recommender System in E-learning

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Executive Summary

A course Recommender System plays an important role in predicting the course selection by student. Here the authors consider the real data from Moodle course of their college & they try to obtain the result using Weka. Association rule algorithms are used to find out the best combination of courses in E-Learning. Here in this paper, they consider four association rule algorithms: Apriori Association Rule, PredictiveApriori Association Rule, Tertius Association Rule & Filtered Associator. They compare the result of these four algorithms & present the result. According to their simulation result, they find that Apriori association algorithms perform better than the Predictive Apriori Association Rule, Tertius Association Rule, & Filtered Associator in predicting the course selection based on student choice.

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