Mining Frequent Itemsets Algorithm Based on Compression Matrix

Zi Zhi Lin; Si Hui Shu

doi:10.4028/www.scientific.net/AMM.556-562.3501

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Mining Frequent Itemsets Algorithm Based on...

Mining Frequent Itemsets Algorithm Based on Compression Matrix

Abstract:

Association rule mining is one of the most important and well researched techniques of data mining. The key procedure of the association rule mining is to find frequent itemsets. In this paper, a new mining frequent itemsets algorithm based on matrix is introduced. Frequent itemsets are obtained by compressing the transaction matrix efficiently by a new strategy. The new algorithm optimizes the known mining frequent itemsets algorithms based on matrix given by some researchers in recent years, which greatly reduces the temporal complexity and spatial complexity. It is more feasible especially when the degrees of the frequent itemsets are high.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

3501-3505

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.3501

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Cite this paper

Online since:

May 2014

Authors:

Zi Zhi Lin*, Si Hui Shu

Keywords:

Association Rule, Compression Matrix
, Data Mining (DM), Frequent Itemsets

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* - Corresponding Author

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