A CRITICAL REVIEW OF VARIOUS METHODOLOGIES FOR MINING HIGH UTILITY ITEM SETS FROM A UTILITY DATA SET

Data Mining, also called knowledge Discovery in Database, is one of the latest research area, which has emerged in response to the Tsunami data or the flood of data, world is facing nowadays. It has taken up the challenge to develop techniques that can help humans to discover useful patterns in massive data. One such important technique is utility mining. Frequent item set mining works to discover item set which are frequently appear in transaction database, which can be discover on the basis of support and confidence value of different item set. Using frequent item set mining concept as a base, many researchers have also proposed different new concept on utility based mining of item set. This paper presents an analysis of various methodologies used for mining high utility item sets from a utility data set.