A New Approach to Discover Frequent Patterns Using FP-Graph Model

In this paper an algorithm is proposed for mining frequent itemsets. This paper proposes a new framework to generate frequent Itemsets/Patterns. First, a partitioning technique is used to divide a transaction database TDB into n non-overlapping partitions. Second we use fp-graph model to discover frequent itemsets for each partition. Example illustrating the proposed approach is given. The characteristics of the algorithm are discussed.