Mining High Utility Itemsets using UP Growth with Genetic Algorithm from Data Mart A.Saranya

Abstract: In data mining in order to analyse vast amount of data, Frequent itemset mining play an important role. In practice, Frequent pattern mining cannot meet the tasks of real world problems due to itemsets vary in numerous measures. Hence an evolving technique called Utility-based data mining is used in data mining processes.The utility mining not only considers the frequency but also see the utility associated with the itemsets.The basic idea of utility mining is to extract the itemsets with high utilities, by considering user preferences such as profit,quantity and cost from OLTP systems. In our proposed approach, we are using UP growth with Genetic Algorithm. The approach is that UP growth algorithm would generate Potentially High Utility Itemsets and Genetic Algorithm would optimize and provide the High Utility Item set from it. On comparing with existing algorithm, the proposed approach is performing better in terms of memory utilization