International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 39 - Issue 1 |
Published: February 2012 |
Authors: Sunita B Aher, Lobo L.M.R.J |
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Sunita B Aher, Lobo L.M.R.J . A Comparative Study of Association Rule Algorithms for Course Recommender System in E-learning. International Journal of Computer Applications. 39, 1 (February 2012), 48-52. DOI=10.5120/4788-7021
@article{ 10.5120/4788-7021, author = { Sunita B Aher,Lobo L.M.R.J }, title = { A Comparative Study of Association Rule Algorithms for Course Recommender System in E-learning }, journal = { International Journal of Computer Applications }, year = { 2012 }, volume = { 39 }, number = { 1 }, pages = { 48-52 }, doi = { 10.5120/4788-7021 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2012 %A Sunita B Aher %A Lobo L.M.R.J %T A Comparative Study of Association Rule Algorithms for Course Recommender System in E-learning%T %J International Journal of Computer Applications %V 39 %N 1 %P 48-52 %R 10.5120/4788-7021 %I Foundation of Computer Science (FCS), NY, USA
A course Recommender System plays an important role in predicting the course selection by student. Here we consider the real data from Moodle course of our college & we 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 we consider four association rule algorithms: Apriori Association Rule, PredictiveApriori Association Rule, Tertius Association Rule & Filtered Associator. We compare the result of these four algorithms & present the result. According to our simulation result, we 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.