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An Effective Method for Association Rule Mining based on Transactional Matrix
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 39 - Number 9 |
| Year of Publication: 2012 |
| Authors: Harpreet Singh, Renu Dhir |
10.5120/4847-7118
|
Harpreet Singh, Renu Dhir . An Effective Method for Association Rule Mining based on Transactional Matrix. International Journal of Computer Applications. 39, 9 ( February 2012), 13-15. DOI=10.5120/4847-7118
Abstract
Focus of this paper is to present a new method based on transactional matrix for finding association rules more efficiently. Apriori algorithm is one of the classical algorithms for finding association rules, but it has limitations of number of times database scanned is too large and number of candidate itemsets generated is large.To reduce these two limitations a new method tries to find the association rules directly from a matrix which is generated from the transactional database .
References
- Jiawei Han and Micheline Kamber, (2001), “Data mining Concepts and Techniques”, Morgan kaufman academic press
- R.Agrawal, “Mining association rules between sets of items in large databases”, Proceeding of the 1993 ACM SIGMOD conference, Washington, pp.207-216
- Changsheng Zhang and Jing Raun, (2009), “A Modified Apriori Algorithm with its application in Instituting Cross-Selling strategies of the Retail Industry”, pp.515-518
- Wanjun Yu, Xiachun Wang and et.al, (2008), “The Research of Improved Apriori Algorithm for Mining Association Rules”, pp. 513-516
- Dongme Sun and et.al, (2007), “An algorithm to improve the effectiveness of Apriori Algorithm”, In Proc. 6th ICE Int. Conf. on Cognitive Informatics”, pp.385-390
- Sixue Bai, Xinxi Dai, (2007), “An efficiency Apriori algorithm:P_matrix algorithm”, First International Symposium on Data, Privacy and E-Commerce, pp.101-103
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