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AlZoubi, Wael Ahmad
- A Survey of Clustering Algorithms in Association Rules Mining
Abstract Views :209 |
PDF Views:105
Authors
Affiliations
1 Applied Science Department, Ajloun University College, Balqa Applied University, JO
1 Applied Science Department, Ajloun University College, Balqa Applied University, JO
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 11, No 2 (2019), Pagination: 17-25Abstract
The main goal of cluster analysis is to classify elements into groupsbased on their similarity. Clustering has many applications such as astronomy, bioinformatics, bibliography, and pattern recognition. In this paper, a survey of clustering methods and techniques and identification of advantages and disadvantages of these methods are presented to give a solid background to choose the best method to extract strong association rules.References
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- Cluster based Association Rule Mining for Courses Recommendation System
Abstract Views :251 |
PDF Views:134
Authors
Affiliations
1 Applied Science Department, Ajloun University College, Balqa Applied University, JO
1 Applied Science Department, Ajloun University College, Balqa Applied University, JO
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 11, No 6 (2019), Pagination: 13-19Abstract
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.References
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- Tsay, Y.-J. & Chiang, J.-Y. 2005. CBAR: an efficient method for mining association rules. Knowledge-Based Systems 18 (2005), pp. 99–105.
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- 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