%0 Journal Article
	%A Elsayeda M. Elgaml and  Dina M. Ibrahim and  Elsayed A. Sallam 
	%D 2015
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 101, 2015
	%T Improved FP-growth Algorithm with Multiple Minimum Supports Using Maximum Constraints
	%U https://publications.waset.org/pdf/10001311
	%V 101
	%X Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy. 

	%P 1122 - 1129