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Bench Marking Frequent Item set Mining Models and Algorithms: Current State of the Art

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 67 - Number 22
Year of Publication: 2013
Authors:
A Muralidhar
V. Pattabiraman
10.5120/11531-7391

A Muralidhar and V Pattabiraman. Article: Bench Marking Frequent Item set Mining Models and Algorithms: Current State of the Art. International Journal of Computer Applications 67(22):43-51, April 2013. Full text available. BibTeX

@article{key:article,
	author = {A Muralidhar and V. Pattabiraman},
	title = {Article: Bench Marking Frequent Item set Mining Models and Algorithms: Current State of the Art},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {67},
	number = {22},
	pages = {43-51},
	month = {April},
	note = {Full text available}
}

Abstract

Identifying the association rules in colossal datasets is possessing elevated level of presence in data mining or data exploration. As a consequence, countless algorithms are approximated to deal alongside this issue. The two setbacks ambitious considering this outlook are: ascertaining all frequent item sets and to produce limits from them. This document is for the most portions aimed at pondering of past scrutiny, present useful rank and to ascertain the gaps of them alongside present ambitious information. Here, early subject, as it acquires extra time to process, is computationally expensive. Current discover targeted on these algorithms and their connected issues.

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