计算机科学 ›› 2012, Vol. 39 ›› Issue (3): 135-138.

• 数据库与数据挖掘 • 上一篇    下一篇

基于线性链表的模糊关联规则挖掘

刘青宝,王文熙,王万军   

  1. (国防科学技术大学信息系统工程重点实验室 长沙410073)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Linear Linklist Based Algorithm for Fuzzy Association Rule Mining

LIU Qing-bao,WANG Wen-xi,WANG Wan-jun   

  • Online:2018-11-16 Published:2018-11-16

摘要: 为改进现有模糊关联规则挖掘算法的不足,提出了一种基于线性链表的模糊关联规则挖掘算法。算法利用线性链表只存储有用的事务数据库信息,并不断利用前期的运算结果对之进行简化,减少了数据的存储开销及扫描时间,降低了算法的时间复杂度,提高了算法的效率。比较分析以及实验表明,该算法对于挖掘模糊关联规则是快速而有效的。

关键词: 数据挖掘,模糊关联规则,线性链表

Abstract: In order to improve the efficiency of existing fuzzy association rule mining algorithms, we presented a linear linklist based algorithm for fuzzy association rule mining. Utilizing the linear hnklist our algorithm only records the information of the tran-suctions which arc useful for counting the support of the frequent itemset, and simplifies the transuctions information according to the previous results,which reduces the cost of data storage and increases the running efficiency. Experiments demonstrate that our method is efficient in fuzzy association rule mining.

Key words: Data mining, Fuzzy association rule, Linear linklist

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