Finding the Frequent Pattern in a Database - A Study on the Apriori Algorithm
Najlaa AlHuwaishel, Maram AlAlwan, Ghada Badr
2014
Abstract
This paper is a study on the frequent pattern mining using the Apriori algorithm. We will present the concept of data mining in a high level and explain how the frequent pattern is mined. We will talk about the Apriori algorithm and the problem with this algorithm followed by exploration of some algorithms that considered as an update on the Apriori algorithm in order to enhance the efficiency problem that we explained. We will also compare the selected algorithms taking under consideration: 1.Number of database scan. 2.Number of generated candidate lists. 3.Memory usage.
References
- Jiawei Han and Micheline Kamber, "Data Mining: Concepts and Techniques, Second Edition," 2006.
- Akhilesh Tiwari, Rajendra K. Gupta and Dev Prakash Agrawal, "A Novel Algorithm for Mining Frequent Item-set From Larg Database", In International Journal of Information Technology and Knowledge Management, Volume 2, No. 2, July-December 2009, pp. 223-229.
- Libing Wu, KuiGong, Fuliang Guo, XiaohuaGe, Yilei Shan, "Research on Improving Apriori Algorithm Based on Interested Table", 2010 IEEE, pp.422-426.
- Sheng Chai, Jia Yang, Yang Cheng," The Research of Improved Apriori Algorithm for Mining Association Rules ",2007 IEEE.
- Anurag Choubey, Ravindra Patel, J.L. Rana," A Survey of Efficient Algorithms and New Approach for Fast Discovery of Frequent Itemset for Association Rule Mining (DFIARM) ", In International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231- 2307, Volume-1, Issue-2, May 2011, pp.62-67.
- Tang Junfang, " An Improved Algorithm of Apriori Based on Transaction Compression", In 2nd International Conference on Control, Instrumentation and Automation (ICCIA), 2011, pp.356-358.
- Rui Chang, Zhiyi Liu, " An Improved Apriori Algorithm", In International Conference on Electronics and Optoelectronics (ICEOE),2011, pp.476-478.
- Preetham Kumar, Ananthanarayana V S, "Parallel Method for Discovering Frequent Itemsets Using Weighted Tree Approach", In International Conference on Computer Engineering and Technology,2009, pp.124- 128.
- Li Tu, Ling Chen, Shan Zhang, "Efficient Algorithms with Time Fading Model for Mining Frequent Items over Data Stream", In International Conference on Industrial and Information Systems, 2009, pp.403-408.
- R.M. Karp, S. Shenker, and C.H. Papadimitriou, "A simple algorithm for finding frequent elements in streams and bags", presented at ACM Transactions on Database Systems, Vol. 28, No. 1, March 2003, pp.51- 55.
- Pramod S, Vyas O.P, "Survey on Frequent Item set Mining Algorithms," presented at International Journal of Computer Applications, Volume 1 - No. 15 pp.86-91.
Paper Citation
in Harvard Style
AlHuwaishel N., AlAlwan M. and Badr G. (2014). Finding the Frequent Pattern in a Database - A Study on the Apriori Algorithm . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 388-396. DOI: 10.5220/0005147703880396
in Bibtex Style
@conference{kdir14,
author={Najlaa AlHuwaishel and Maram AlAlwan and Ghada Badr},
title={Finding the Frequent Pattern in a Database - A Study on the Apriori Algorithm},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},
year={2014},
pages={388-396},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005147703880396},
isbn={978-989-758-048-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - Finding the Frequent Pattern in a Database - A Study on the Apriori Algorithm
SN - 978-989-758-048-2
AU - AlHuwaishel N.
AU - AlAlwan M.
AU - Badr G.
PY - 2014
SP - 388
EP - 396
DO - 10.5220/0005147703880396