A Weighted Association Rules Mining Algorithm with Fuzzy Quantitative Constraints

2013 ◽  
Author(s):  
Qibing Lu ◽  
Buyun Sheng
Keyword(s):  
Association Rules ◽  
Association Rules Mining ◽  
Weighted Association Rules ◽  
Mining Algorithm

An Efficient Weighted Association Rules Mining Algorithm

2013 ◽  
Vol 333-335 ◽  
pp. 1247-1250 ◽  
Author(s):  
Na Xin Peng
Keyword(s):  
Association Rules ◽  
Frequent Itemsets ◽  
Experimental Results ◽  
Apriori Algorithm ◽  
Association Rules Mining ◽  
Fuzzy Association Rules ◽  
Weighted Association Rules ◽  
Mining Algorithm ◽  
Pruning Strategy

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.

Weighted Association Rules Mining Algorithm Research

2012 ◽  
Vol 241-244 ◽  
pp. 1598-1601
Author(s):  
Jun Tan
Keyword(s):  
Association Rules ◽  
Frequent Itemsets ◽  
Experimental Results ◽  
Apriori Algorithm ◽  
Association Rules Mining ◽  
Fuzzy Association Rules ◽  
Weighted Association Rules ◽  
Mining Algorithm ◽  
Pruning Strategy ◽  
Mining Algorithms

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

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