Paper Title
Mining And Hiding Of Sensitive Association Rule By Using Improved Apriori Algorithm

Abstract
Many algorithms are proposed by researchers to find association rules. Now a day, association rule plays an important role. The Apriori algorithm is the basic algorithm for mining association rule. Association rule mining is an interesting area of data mining research which discovers correlations between different itemsets in a transaction database. It finds the frequent itemsets with the transactions using an improved Apriori algorithm which further reduces the number of scans in the database. This paper has two sections in first section an improved Apriori algorithm is being presented that efficiently generates association rules. In the second section of this paper a hiding of sensitive association rule by using an improved Apriori algorithm. The main approach of association rule hiding algorithms to hide some generated association rules, by increase or decrease the support or the confidence of the rule without producing any side effects. Keywords- Association rules, confidence, support, Minimum Support Threshold (MST), Minimum Confidence Threshold (MCT), Rule hiding.

Author - Shintre Sonali Sambhaji, Kalyankar Pravin P.

Published : Volume-2, Issue-3  ( Mar, 2015 )

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