Fast Algorithm for Mining Global Frequent Itemsets Based on Distributed Database

There were some traditional algorithms for mining global frequent itemsets. Most of them adopted Apriori-like algorithm frameworks. This resulted a lot of candidate itemsets, frequent database scans and heavy communication traffic. To solve these problems, this paper proposes a fast algorithm for mining global frequent itemsets, namely the FMGFI algorithm. It can easily get the global frequency for any itemsets from the local FP-tree and require far less communication traffic by the searching strategies of top-down and bottom-up. It effectively reduces existing problems of most algorithms for mining global frequent itemsets. Theoretical analysis and experimental results suggest that the FMGFI algorithm is fast and effective