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An Analysis on Association Rule Mining Techniques

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IJCA Special Issue on International Conference on Computing, Communication and Sensor Network
© 2013 by IJCA Journal
CCSN2012 - Number 4
Year of Publication: 2013
Authors:
Ish Nath Jha
Samarjeet Borah

Ish Nath Jha and Samarjeet Borah. Article: An Analysis on Association Rule Mining Techniques. IJCA Special Issue on International Conference on Computing, Communication and Sensor Network CCSN2012(4):40-45, March 2013. Full text available. BibTeX

@article{key:article,
	author = {Ish Nath Jha and Samarjeet Borah},
	title = {Article: An Analysis on Association Rule Mining Techniques},
	journal = {IJCA Special Issue on International Conference on Computing, Communication and Sensor Network},
	year = {2013},
	volume = {CCSN2012},
	number = {4},
	pages = {40-45},
	month = {March},
	note = {Full text available}
}

Abstract

Association rule mining is a subfield of Data mining. It is a popular and widely used method to extract interesting and useful patterns from large sets of data. The first Rule Mining Algorithm was formulated by R. Agrawal in 1993. After the Apriori Algorithm formulated by R. Agrawal, many other algorithms have been proposed. Each of these algorithms has its own advantages and disadvantages over the others. The major issues of concern are the cost efficiency in terms of memory utilization, interestingness of the rules generated, influence of the minimum support level specified on the rules generated, the ability to discover relationships not only quantitatively but also qualitatively and the processing efficiency of the algorithm. This paper provides a comparative analysis on the classical Apriori algorithm along with some other association rule mining algorithms.

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