The research of improved association rules mining Apriori algorithm

Author(s):  
Huiying Wang ◽  
Xiangwei Liu
2013 ◽  
Vol 333-335 ◽  
pp. 1247-1250 ◽  
Author(s):  
Na Xin Peng

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.


2011 ◽  
Vol 179-180 ◽  
pp. 55-59
Author(s):  
Ping Shui Wang

Association rule mining is one of the hottest research areas that investigate the automatic extraction of previously unknown patterns or rules from large amounts of data. Finding association rules can be derived based on mining large frequent candidate sets. Aiming at the poor efficiency of the classical Apriori algorithm which frequently scans the business database, studying the existing association rules mining algorithms, we proposed a new algorithm of association rules mining based on relation matrix. Theoretical analysis and experimental results show that the proposed algorithm is efficient and practical.


2012 ◽  
Vol 263-266 ◽  
pp. 3060-3063 ◽  
Author(s):  
Yi Tao Zhang ◽  
Wen Liang Tang ◽  
Cheng Wang Xie ◽  
Ji Qiang Xiong

A VPA algorithm is proposed to mining the association rules in the privacy preserving data mining, where data is vertically partitioned. The VSS protocol was used to encrypt the vertically data, which was owned by different parties. And the private comparing protocol was adopted to generate the frequent itemset. In VPA the ID numbers of the recordings were employed to keep the consistency of the data among different parties, which were saved in ID index array. The VPA algorithm can generate association rules without violating the privacy. The performance of the scheme is validated against representative real and synthetic datasets. The results reveal that the VPA algorithm can do the same in finding frequent itemset and generating the consistent rules, as it did in Apriori algorithm, in which the data were vertically partitioned and totally encrypted.


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