An Improved Apriori Algorithm Based on Association Analysis

Yubo Jia, Guanghu Xia, Hongdan Fan, Qian Zhang, Xu Li
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引用次数: 19

Abstract

Association Rules Mining is an important branch of Data Mining Technology, of which Apriori Algorithm is the most influential and classic one. After discussing and analyzing the basic concept of Association Rules Mining, this paper proposes an improved algorithm based on a combination of Data Division and Dynamic Item sets Counting. Analysis of the improved algorithm proves that it can effectively improve the performance of Data Mining.
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一种基于关联分析的改进Apriori算法
关联规则挖掘是数据挖掘技术的一个重要分支,其中Apriori算法是最具影响力和最经典的一种。在对关联规则挖掘的基本概念进行讨论和分析的基础上,提出了一种基于数据分割和动态项集计数相结合的改进算法。对改进算法的分析表明,改进算法可以有效地提高数据挖掘的性能。
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