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Volume & Issue no: Volume 3, Issue 6, November - December 2014

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Title:
Study of Mining and Hiding of Sensitive Association Rule
Author Name:
Shintre Sonali Sambhaji, Prof. Kalyankar Pravin P.
Abstract:
Abstract This paper is organized into two approaches. In first approach an Improved Apriori algorithm is being presented that efficiently generates association rules. This reduces unnecessary database scan at the time of forming frequent large itemsets. In second approach we have tried to hide sensitive association rule by using an improved Apriori algorithm. In this paper, we have used an approach that strategically modifies fewer transactions in a transaction database to decrease support and confidence of a sensitive rule without producing any side effects. Thus, in the paper, we efficiently generate frequent itemset by applying Improved Apriori algorithm and generated association rules by applying minimum support and minimum confidence and then identify the sensitive association rules. Index Terms:-Association rules, confidence, Data mining methods and Algorithm, Minimum Support Threshold (MST), Minimum Confidence Threshold (MCT), Rule hiding.
Cite this article:
Shintre Sonali Sambhaji, Prof. Kalyankar Pravin P. , " Study of Mining and Hiding of Sensitive Association Rule" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 3, Issue 6, November - December 2014 , pp. 221-226 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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