An Efficient Weighted Association Rules Mining Algorithm

Na Xin Peng

doi:10.4028/www.scientific.net/AMM.333-335.1247

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 333-335An Efficient Weighted Association Rules Mining...

An Efficient Weighted Association Rules Mining Algorithm

Abstract:

Aiming at the problem that most of weighted association rules algorithm have not the anti-monotonicity, this paper presents a weighted support-confidence framework which supports anti-monotonicity. On this basis, Boolean weighted association rules algorithm and weighted fuzzy association rules algorithm are presented, which use pruning strategy of Apriori algorithm so as to improve the efficiency of frequent itemsets generated. Experimental results show that both algorithms have good performance.

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Periodical:

Applied Mechanics and Materials (Volumes 333-335)

Pages:

1247-1250

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.333-335.1247

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Online since:

July 2013

Authors:

Na Xin Peng

Keywords:

Anti-Monotonicity, Apriori Algorithm, Weighted Association Rule, Weighted Support

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References

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