The Research of Improved Apriori Algorithm

Bi Xujing () and Xu Weixiang ()
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Bi Xujing: Beijing Jiaotong University
Xu Weixiang: Beijing Jiaotong University

A chapter in LISS 2012, 2013, pp 1007-1012 from Springer

Abstract: Abstract According to the weakness of Apriori algorithm, such as too many scans of the database and vast candidate itemsets, this chapter proposes an improved Apriori algorithm which scans the database only once by using arrays to store data. In addition, the new algorithm sorts the frequent itemsets from small to large according to their supports before they are connected, so as to optimize the connection strategy and eliminate redundant candidate itemsets as far as possible. Experimental result shows that the algorithm can save memory space and improve the efficiency of the algorithm.

Keywords: Association rule; Apriori algorithm; Array; Frequent itemsets; Candidate itemsets (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-32054-5_141

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DOI: 10.1007/978-3-642-32054-5_141

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