Parallel algorithm for mining frequent itemsets

Parallel mining frequent itemsets is a key issue in data mining research. A parallel mining algorithm PMFI in distributed database is proposed in this paper, which attempts to make each processor to do independently and decrease the number of candidate of global frequent itemsets according to the relation between local frequent itemsets and global frequent itemsets. Thus, PMFI uses far less communication overhead and fewer synchronization steps, improves efficiency of mining global frequent itemsets.