Implementing reverse up growth tracking approach under distributed data mining

Abstract

Data mining is the methodology which discovers useful and hidden information from large databases. Many researchers have proposed innumerable algorithms in the field of data mining. In this system improvised UP-growth is considered for mining high utility itemset from potential high utility itemset and improvised under different constraints. The node utility and reorganised transaction utility are the aspects considered as the key term in the proposed system which are manipulated using the technique as in UP-growth. However, mining potential high utility itemset from RTU using UP-growth needs number of tree traversals. This is reduced in the proposed system by introducing bottom-up approach and merging certain manipulations. However, working the system as a sequential process will be time consuming. Distributed environment is considered in the proposed system to overwhelm the problem in existing methodology.