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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
10.5120/ijais12-450412
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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

    @article{key:article,
    	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"
    }
    

Abstract

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.

Reference

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Keywords

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