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A Novel Algorithm for Cross Level Frequent Pattern Mining in Multidatasets

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 37 - Number 6
Year of Publication: 2012

B.Jayanthi and Dr.K.Duraiswamy. Article: A Novel Algorithm for Cross Level Frequent Pattern Mining in Multidatasets. International Journal of Computer Applications 37(6):30-35, January 2012. Full text available. BibTeX

	author = {B.Jayanthi and Dr.K.Duraiswamy},
	title = {Article: A Novel Algorithm for Cross Level Frequent Pattern Mining in Multidatasets},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {37},
	number = {6},
	pages = {30-35},
	month = {January},
	note = {Full text available}


Frequent pattern mining has become one of the most popular data mining approaches for the analysis of purchasing patterns. There are techniques such as Apriori and FP-Growth, which were typically restricted to a single concept level. We extend our research to discover cross - level frequent patterns in multi-level environments. Unfortunately, little research has been paid to this research area. Mining cross - level frequent pattern may lead to the discovery of mining patterns at different levels of hierarchy. In this study a transaction reduction technique with FP-tree based bottom up approach is used for mining cross-level pattern. This method is using the concept of reduced support


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