An Efficient Approach to Discover High Utility Itemset From Transactional Database

Computer Engineearin

Data Mining is the process of evaluating data from different outlooks and summarizing it into useful information. It can be defined as the process that extracts information contained in very large database. Traditional Data mining methods have been focused on to finding a correlation between items which are frequently appearing in the database. And relative importance of each item is not consider in frequent pattern mining. High utility mining is an area research where utility based mining can be done. Mining high utility itemset from a transactional database refers to the discovery of itemset with high utility in a terms like weight, unit profit or value. In past algorithm used to mine high utility itemset takes more time to execute and memory. In this paper we proposed an algorithm which uses a tree structure and an array to store the transaction value and then proposed algorithm find the high utility itemset. An extensive experimental study with four real- life datasets shows that our proposed algorithm executes faster than FHM algorithm.

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