A Prefixed-Itemset-Based Improvement For Apriori Algorithm

Shoujian Yu; Yiyang Zhou

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A Prefixed-Itemset-Based Improvement For Apriori Algorithm

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arxiv 1601.01746 v1 pith:4ZYMOERY submitted 2016-01-08 cs.DS cs.DB

A Prefixed-Itemset-Based Improvement For Apriori Algorithm

Shoujian Yu , Yiyang Zhou This is my paper

classification cs.DS cs.DB

keywords algorithmaprioriassociationclassicaldataefficiencyprefixed-itemset-basedrules

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Association rules is a very important part of data mining. It is used to find the interesting patterns from transaction databases. Apriori algorithm is one of the most classical algorithms of association rules, but it has the bottleneck in efficiency. In this article, we proposed a prefixed-itemset-based data structure for candidate itemset generation, with the help of the structure we managed to improve the efficiency of the classical Apriori algorithm.

A Prefixed-Itemset-Based Improvement For Apriori Algorithm

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