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Mining of frequent Itemset using PAFI and Transaction Reduction Method

Anil Vasoya, Rekha Sharma Published in Data Mining

IJAIS Proceedings on International Conference and workshop on Advanced Computing 2013
Year of Publication: 2013
© 2012 by IJAIS Journal
10.5120/icwac1335
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  1. Anil Vasoya and Rekha Sharma. Article: Mining of frequent Itemset using PAFI and Transaction Reduction Method. IJAIS Proceedings on International Conference and workshop on Advanced Computing 2013 ICWAC(3):20-24, June 2013. BibTeX

    @article{key:article,
    	author = "Anil Vasoya and Rekha Sharma",
    	title = "Article: Mining of frequent Itemset using PAFI and Transaction Reduction Method",
    	journal = "IJAIS Proceedings on International Conference and workshop on Advanced Computing 2013",
    	year = 2013,
    	volume = "ICWAC",
    	number = 3,
    	pages = "20-24",
    	month = "June",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Now a day, Mining of Association rules in large database is the challenging task. An Apriori algorithm is widely used to find out the frequent item sets from large database. But it has some limitations. It produces overfull candidates while finding the frequent item sets from transactions, i. e. the algorithm needs to scan database repetitively while finding frequent item sets. It will be inefficient in large database and also it requires more I/O load while accessing the database frequently. To solve the bottleneck of the Apriori algorithm, PAFI and Matrix based method used in proposed system.

Reference

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Keywords

PAFI, Apriori algorithm, frequent Itemset, clustering, AND operation, affair