Fast Distributed Algorithm of Mining Global Frequent Itemsets

Abstract:

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Most distributed algorithms of mining global frequent itemsets worked on net structure network and adopted Apriori-like algorithm. Whereas there were some problems in these algorithms: a lot of candidate itemsets and heavy communication traffic. Aiming at these problems, this paper proposed a fast distributed algorithm of mining global frequent itemsets, namely, FDMGFI algorithm, which set centre node. FDMGFI algorithm made computer nodes compute local frequent itemsets independently with FP-growth algorithm, then the centre node exchanged data with other computer nodes and combined, finally, global frequent itemsets were gained. FDMGFI algorithm required far less communication traffic by the searching strategies of top-down and bottom-up. Theoretical analysis and experimental results suggest that FDMGFI algorithm is fast and effective.

Info:

Periodical:

Advanced Materials Research (Volumes 219-220)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

191-194

DOI:

10.4028/www.scientific.net/AMR.219-220.191

Citation:

B. He "Fast Distributed Algorithm of Mining Global Frequent Itemsets", Advanced Materials Research, Vols. 219-220, pp. 191-194, 2011

Online since:

March 2011

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Price:

$35.00

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