As far as we know, a little research of global maximum frequent itemsets had been done. Therefore, a fast mining algorithm of global maximum frequent itemsets was proposed, namely, FMAGMFI algorithm. Firstly, each computer nodes compute local maximum frequent itemsets with DMFIA algorithm and local FP-tree. Secondly, the center node combined local maximum frequent itemsets. Finally, global maximum frequent itemsets were gained by the searching strategy of top-bottom. Adopting FP-tree structure, FMAGMFI algorithm greatly reduces runtime compared with Apriori-like algorithms. Theoretical analysis and experimental results suggest that FMAGMFI algorithm is efficient.


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    Titel :

    Fast Mining Algorithm of Global Maximum Frequent Itemsets


    Weitere Titelangaben:

    Adv.Intel.,Soft Computing


    Beteiligte:
    Xie, Anne (Herausgeber:in) / Huang, Xiong (Herausgeber:in) / He, Bo (Autor:in)


    Erscheinungsdatum :

    2012-01-01


    Format / Umfang :

    6 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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