Association Rule Mining has been the area of interest for many researchers for a long time and continues to be the same. It is one of the important tasks of data mining. It aims at discovering relationships among various items in the database. There are several algorithms of which Apriori is the classical and most famous algorithm. But in classical Apriori algorithm human intervention is required for the threshold values of support and confidence. To solve this problem, an automated Apriori algorithm is proposed in this paper, where correlation coefficient of the items has been considered. This paper also presents a comparison between original Apriori Algorithm and our automated Apriori Algorithm through experiments
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