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Mining Non-redundant Frequent Patterns in Taxonomy Datasets using Concept Lattices

R. Vijaya Prakash, A. Govardhan, Ssvn Sarma Published in Data Mining

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
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  1. Vijaya R Prakash, A Govardhan and Ssvn Sarma. Article: Mining Non-redundant Frequent Patterns in Taxonomy Datasets using Concept Lattices. International Journal of Applied Information Systems 3(9):1-6, August 2012. BibTeX

    	author = "R. Vijaya Prakash and A. Govardhan and Ssvn Sarma",
    	title = "Article: Mining Non-redundant Frequent Patterns in Taxonomy Datasets using Concept Lattices",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 3,
    	number = 9,
    	pages = "1-6",
    	month = "August",
    	note = "Published by Foundation of Computer Science, New York, USA"


In general frequent itemsets are generated from large data sets by applying various association rule mining algorithms, these produce many redundant frequent itemsets. In this paper we proposed a new framework for Non-redundant frequent itemset generation using closed frequent itemsets without lose of information on Taxonomy Datasets using concept lattices.


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Non Redundant, Frequent Patterns, Concept Lattice, Association Rules, Itemset