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Data mining is a technique to process data, select it, integrate it and recover some useful information. Association Rule Mining (ARM) has been the area of interest for many researchers for a long time and continues to be the same. The DBSCAN algorithm is a popular algorithm in Data Mining field as it has the ability to mine the noiseless arbitrary shape Clusters in an attractive way. To improve the performance of the new algorithm and without losing the quality of Clusters, we have used the Memory Effect in DBSCAN Algorithm approach. In this paper we propose a new algorithm for mining the density based clusters and the algorithm is intelligent enough to mine the clusters with different densities for improved Association mining rules. One of the disadvantages of DBSCAN is its inability in identifying clusters with different densities in a dataset.
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