Parallel Association Rule Mining on Heterogeneous System
Association Rule Mining from transaction - oriented databases is one of the important process that finds relation between items and plays important role in decision making. Parallel algorithms are required because of large size of the database to be mined. Most of the algorithms designed were for homogeneous system uses static load balancing technique which is far from reality. A parallel algorithm for heterogeneous system is regarded as one of the most promising platforms for association rule mining. In this paper, the authors propose a simple parallel algorithm for association rule mining on heterogeneous system with dynamic load balancing based on Par-Maxclique algorithm.