计算机工程与应用 ›› 2006, Vol. 42 ›› Issue (29): 12-.

• 博士论坛 • 上一篇    下一篇

降序加权join半概念格快速挖掘算法

周涛、张艳宁、袁和金、陆惠玲

  

  1. 陕西理工学院计算机科学系
  • 收稿日期:2006-07-04 修回日期:1900-01-01 出版日期:2006-10-11 发布日期:2006-10-11
  • 通讯作者: 周涛 zhout123 zhout123

Fast Mining Algorithm Based on Descend Weighted join half Concept Lattice

Tao zhou,,,   

  1. 陕西理工学院计算机科学系
  • Received:2006-07-04 Revised:1900-01-01 Online:2006-10-11 Published:2006-10-11
  • Contact: Tao zhou

摘要: 摘 要:通过分析Eclat算法,对完全概念格按照支持度进行了裁减,得到了一个向下封闭的降序join半概念格,在构造半概念格的同时计算出每一个项集的支持度作为其权值,最后基于降序加权join半概念格对Eclat算法进行了改进,裁减了概念格中大量的冗余的连接,给出了一个快速的关联规则挖掘算法。经过分析,该算法与Eclat算法相比,效率更高。

关键词: 数据挖掘, Eclat算法, Join半概念格, 半概念格

Abstract: Abstract: Eclat algorithm is discussed and analyzed completely. Through Pruning entireness lattice depend on support, a descend weighted join half concept lattice is obtained that is closed downward, support for each node of concept lattice is calculated as constructing concept lattice. At last, a new fast mining association rules is presented. Its efficiency is more high than Eclat algorithm through analysis.

Key words: Data Mining, Eclat Algorithm, Join half concept lattice, half concept lattice