Frequent Itemsets Generation using Efficient Utility Mining Algorithm

Abstract

Utility-based data mining is a rapidly developing research area in all types of utility factors in data mining processes. High utility mining is an emerging domain in Utility based data mining which is aimed at finding only itemsets that possess high utility value. Many algorithms are aiming at finding high utility itemsets. A well-known algorithm called Improved Fast Utility Mining (iFUM) lacks in functional accuracy when applied to large volumes of database. Hence, an Efficient Utility Mining (EUM) algorithm proposed in this paper to find all utility itemsets within the given utility threshold and timestamp. Moreover, a novel method is proposed in this paper for generating different types of utility frequent itemsets such as High Utility High Frequency (HUHF), High Utility Low Frequency (HULF), Low Utility High Frequency (LUHF), Low Utility Low Frequency (LULF) using a combination of Efficient Utility Mining (EUM) algorithm and Frequent Itemset Mining (FIM) algorithm for a given time interval.