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An Improved Apriori Algorithm Based on Association Analysis

机译:基于关联分析的改进Apriori算法

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摘要

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.
机译:关联规则挖掘是数据挖掘技术的重要分支,其中Apriori算法是最有影响力的经典算法。在讨论和分析了关联规则挖掘的基本概念之后,本文提出了一种基于数据划分和动态项目集计数相结合的改进算法。对改进算法的分析表明,该算法可以有效提高数据挖掘的性能。

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