An Improved Approach for Mining High Utility Item Set from Large and Dynamic Data Set

Utility mining is an extension of pattern mining. Utility means weight, profit, cost, quantity or any useful entity on which business environment can depend on. Utility mining is an important technique for mining patterns through utility. Utility mining provides sufficient information about the product. Several algorithms have been developed for mining high utility itemsets. Efficiency is a big factor for improvement in the existing algorithms. Efficiency can be measured in term of execution time, memory requirement or arithmetic complexity. In this paper we present a novel approach for mining high utility item set with the help of data compactions techniques. Our proposed algorithm not only reduces the data base size during scanning of data set but also reduces number of candidates and lessens arithmetic calculation that provides a big advantage over the previous algorithms.