关联规则挖掘的Apriori算法的改进

黄进, 尹治本

黄进, 尹治本. 关联规则挖掘的Apriori算法的改进[J]. 电子科技大学学报, 2003, 32(1): 76-79.
引用本文: 黄进, 尹治本. 关联规则挖掘的Apriori算法的改进[J]. 电子科技大学学报, 2003, 32(1): 76-79.
Huang Jin, Yin Zhiben. Improvement of Apriori Algorithm for Mining Association Rules[J]. Journal of University of Electronic Science and Technology of China, 2003, 32(1): 76-79.
Citation: Huang Jin, Yin Zhiben. Improvement of Apriori Algorithm for Mining Association Rules[J]. Journal of University of Electronic Science and Technology of China, 2003, 32(1): 76-79.

关联规则挖掘的Apriori算法的改进

详细信息
    作者简介:

    黄进 男 25岁 硕士 主要从事数据挖掘和知识发现方面的研究

  • 中图分类号: TP311

Improvement of Apriori Algorithm for Mining Association Rules

  • 摘要: 提出一种将Apriori算法与散列技术和事务压缩技术相结合的改进算法,研究了散列函数的构造及其对算法效率的影响,分析了事务压缩技术的原理及其实现方法,用实例给出了原算法与改进算法的实现步骤,结果表明,新算法减小了存储空间,提高了算法的效率,并改进了数据挖掘技术的性能。
    Abstract: This paper puts forward an enhanced algorithm which associates Apriori with hash technique and transaction reduction technique. The construction and the influence to algorithm's efficiency of hash function is studied.The theory and realizable method of transaction reduction technique are also analyzed.And then the realizable steps of the foold algorithm and the enhanced algorithm are made out through an example. The result shows that the new algorithm promotes the algorithm' efficiency and at the same time improves the performance of the data mining technique through cutting down the store space.
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出版历程
  • 收稿日期:  2002-08-27
  • 刊出日期:  2003-02-14

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