An Algorithm for Mining Multidimensional Positive and Negative Association Rules

Abstract:

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Research on negative association rule in multidimensional data mining is few. In this paper, an algorithm MPNAR is put forward to mine positive and negative association rules in multidimensional data. With the help of the basis of the minimum support and minimum confidence, this algorithm divided the multidimensional datasets into infrequent itemsets and frequent itemsets. The negative association rules could be mined from infrequent itemsets. Relative to the single positive association rule mining, the new additional negative association rules need not repeatedly read database because two types of association rules were simultaneously mined. Experiments show that the algorithm method is effective and valuable.

Info:

Periodical:

Advanced Materials Research (Volumes 171-172)

Edited by:

Zhihua Xu, Gang Shen and Sally Lin

Pages:

445-449

DOI:

10.4028/www.scientific.net/AMR.171-172.445

Citation:

H. Jiang et al., "An Algorithm for Mining Multidimensional Positive and Negative Association Rules", Advanced Materials Research, Vols. 171-172, pp. 445-449, 2011

Online since:

December 2010

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Price:

$35.00

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