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Fast mining of global maximum frequent itemsets in distributed database

Bo He

Open publisher page 7 citations

Abstract

The paper proposes an algorithm for fast mining global maximum frequent itemsets(FMMFI) in distributed database,which sets center node.FMMFI algorithm makes computer nodes compute local maximum frequent itemsets independently with discover maximum frequent itemsets algorithm(DMFIA) algorithm and local FP-tree.Then the center node collects data with other computer nodes and combines data.Finally,global maximum frequent itemsets are gained. FMMFI require far less candidate itemsets and communication traffic by using the strategy of top-down.Theoretical analysis and experimental results show the effectiveness of the FMMFI algorithm.

About this research paper

What this paper is about

The paper proposes an algorithm for fast mining global maximum frequent itemsets(FMMFI) in distributed database,which sets center node.FMMFI algorithm makes computer nodes compute local maximum frequent itemsets independently with discover maximum frequent itemsets algorithm(DMFIA) algorithm and local FP-tree.Then the center node collects data with other computer nodes and combines data.Finally,global maximum frequent itemsets are gained. FMMFI require far less candidate itemsets and communication traffic by using the strategy of top-down.Theoretical analysis and experimental results show the effectiveness of the FMMFI algorithm.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The paper proposes an algorithm for fast mining global maximum frequent itemsets(FMMFI) in distributed database,which sets center node.FMMFI algorithm makes computer nodes compute local maximum frequent itemsets independently with discover maximum frequent itemsets algorithm(DMFIA) algorithm and local FP-tree.Then the center node collects data with other computer nodes and combines data.Finally,global maximum frequent itemsets are gained. FMMFI require far less candidate itemsets and communication traffic by using the strategy of top-down.Theoretical analysis and experimental results show the effectiveness of the FMMFI algorithm.

Key concepts: Data mining, Node (physics), Computer science, Center (category theory), Tree (set theory), Distributed database, Algorithm, Database

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