A Fast Algorithm for Mining High Utility Itemsets

Utility based data mining is a new research area entranced in all types of utility factors in data mining processes and focused at integrating utility considerations in data mining tasks. A research area within utility based data mining known as high utility mining is aimed at finding itemsets that interpose high utility. The well known efficient algorithm for mining high utility itemsets from large transaction databases is the UMining algorithm. We present here a novel algorithm fast utility mining (FUM) which finds all high utility itemsets within the given utility constraint threshold. It is faster and simpler than the original UMining algorithm. The experimental evaluation on transaction datasets showed that our algorithm executes faster than UMining algorithm and exceptionally faster when more itemsets are identified as high utility itemsets and when the number of distinct items in the database increases. We have also suggested a novel method of generating different types of itemsets such as High Utility and High Frequency itemsets (HUHF), High Utility and Low Frequency itemsets (HULF), Low Utility and High Frequency itemsets (LUHF) and Low Utility and Low Frequency itemsets (LULF) using a combination of FUM and Fast Utility Frequent mining (FUFM) algorithms.