The Algorithm for Mining Global Frequent Itemsets based on Big Data

There were some algorithms for mining global frequent itemsets. Most of them adopted apriori-like algorithm, so that a lot of candidate itemsets were generated. To solve the problems, the algorithm for mining global frequent itemsets based on big data was proposed, namely, MGFI algorithm. MGFI algorithm computed local frequent itemsets by mapreduce, then the center node collected data, finally, global frequent itemsets were got by mapreduce. MGFI algorithm required less communication traffic by the searching strategies of top-down and bottom-up. Theoretical analysis and experimental results suggest that MGFI algorithm is fast and effective. KeywordsData Mining; Global Frequent Itemsets; Big Data; Mapreduce; FP-tree

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