Certain analytical approaches for Scalable association rule mining With optimal search space

Abstract

The analysis of association rules composes a very important task in newlinethe process of data mining Association rules are an important method of newlineregularities within data which have been exclusively studied by the data newlinemining society The extensive objective here is to find intermittent newlineconcurrence of items within a set of transactions The found concurrence newlineitems are called associations newlineMining frequent patterns from a given transaction dataset is not a newlinenegligible task Based on the user specified minimum support value the set of newlineitems that occur frequently has to be identified An important issue involved newlinehere is that the time taken to compute the frequent item sets because when it newlineinvolves large databases there might be lot of possible item sets which need newlineto be evaluated A different approaches in the algorithm tends to allow newlineefficient discovery of frequent patterns newline newline newline