  Association rule mining is an active data mining research area and most ARM
algorithms cater to a centralized environment. Centralized data mining to
discover useful patterns in distributed databases isn't always feasible because
merging data sets from different sites incurs huge network communication costs.
In this paper, an Improved algorithm based on good performance level for data
mining is being proposed. In local sites, it runs the application based on the
improved LMatrix algorithm, which is used to calculate local support counts.
Local Site also finds a centre site to manage every message exchanged to obtain
all globally frequent item sets. It also reduces the time of scan of partition
database by using LMatrix which increases the performance of the algorithm.
Therefore, the research is to develop a distributed algorithm for
geographically distributed data sets that reduces communication costs, superior
running efficiency, and stronger scalability than direct application of a
sequential algorithm in distributed databases.
