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Efficiently Mining Frequent Itemsets using Various Approaches: A Survey

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 55 - Number 7
Year of Publication: 2012
C. A. Dhote
Sheetal Rathi

C A Dhote and Sheetal Rathi. Article: Efficiently Mining Frequent Itemsets using Various Approaches: A Survey. International Journal of Computer Applications 55(7):28-32, October 2012. Full text available. BibTeX

	author = {C. A. Dhote and Sheetal Rathi},
	title = {Article: Efficiently Mining Frequent Itemsets using Various Approaches: A Survey},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {55},
	number = {7},
	pages = {28-32},
	month = {October},
	note = {Full text available}


In this paper we present the various elementary traversal approaches for mining association rules. We start with a formal definition of association rule and its basic algorithm. We then discuss the association rule mining algorithms from several perspectives such as breadth first approach, depth first approach and Hybrid approach. Comparison of the various approaches is done in terms of time complexity and I/O overhead on CPU. Finally, this paper prospects the association rule mining and discuss the areas where there is scope for scalability.


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