Open Access
Subscription Access
Cluster based Association Rule Mining for Courses Recommendation System
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.
Keywords
Collaborative Filtering, Cluster, Association Rules, Recommendation System.
User
Font Size
Information
- Resnick P. and Varian H., Recommender Systems, Communication of the ACM, 40(3), 56-58, March1997.
- Wiranto, Winarko E., Hartati S., and Wardoyo R., Improving the Prediction Accuracy of Multicriteria Collaborative Filtering by Combination Algorithms, International Journal of Advanced Computer Science and Applications, 5(4), pp. 52 - 58, 2014.
- Philip S., Shola P.B., John A.O., Application of Content-Based Approach in Research Paper Recommendation System for a Digital Library, International Journal of Advanced Computer Science and Applications, 5(10), pp. 37-40, 2014.
- Shih Y. and Liu D., Hybrid Recommendation Approaches: Collaborative Filtering via Valuable Content Information, In the Proceedings of the 38th Annual Hawaii International Conference HICSS '05, 2005, 217-223.
- Tsay, Y.-J. & Chiang, J.-Y. 2005. CBAR: an efficient method for mining association rules. Knowledge-Based Systems 18 (2005), pp. 99–105.
- Neha Aggarwal et al. A Mid – Point based k-mean Clustering Algorithm for Data mining. International Journal on Computer Science and Engineering (IJCSE).Vol. 4 No. 06 June 2012. Pp 1174 – 1180.
- Cheng, D. et al. kNN Algorithm with Data-Driven k Value. International Conference on Advanced Data Mining and Applications. December 2014. DOI: 10.1007/978-3- 319-14717-8_39.
- Balabanovic M, Shoham Y. Fab: content-based, collaborative recommendation. Communications of the ACM; 1997 March; 40(3):66-72.
- AlBadarneh, Amer & Jamal AlSakran, An Automated Recommender System for Course Selection. International Journal of Advaned Computer Science and Applications, 2016.
- Raghad Obeidat, Rehab Duwairi, Ahmad Al-Aiad. A Collaborative Recommendation System for Online Courses Recommendations, 2019. International Conference on Deep Learning and Machine Learning in Emerging Applications (Deep- ML), 2019
Abstract Views: 377
PDF Views: 173