Co-occurence of frequent itemsets in Association Rule Mining

paper, we have proposed an algorithm for Association rule mining to find frequent itemsets .This approach is based on Frequent Pattern Tree to find co-occurrence of frequent itemset which will ultimately reduce the scanning of the database resulting in lesser CPU time and is more efficient than the existing FP growth approach. In this approach a relatively small tree is created for each frequent item based on the user defined minimum support so the memory required by data structure is comparatively very low as huge memory is required for storing itemset in data structure in previous approach and also a very simple and non recursive mining process is done.