吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

基于软集上逻辑公式的极大关联规则描述与挖掘方法

冯锋, 张珑耀, 张青   

  1. 西安邮电大学 理学院, 西安 710121
  • 收稿日期:2017-04-05 出版日期:2018-07-26 发布日期:2018-07-31
  • 通讯作者: 冯锋 E-mail:fengnix@hotmail.com

Description and Mining Method of Maximal Association RulesBased on Logical Formulas on Soft Sets

FENG Feng, ZHANG Longyao, ZHANG Qing   

  1. School of Science, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
  • Received:2017-04-05 Online:2018-07-26 Published:2018-07-31
  • Contact: FENG Feng E-mail:fengnix@hotmail.com

摘要: 针对常规关联规则定义中未涉及项域划分的问题, 提出极大关联规则是对常规关联规则的有益补充. 以软集理论和软集逻辑公式为主要工具, 解决了常规关联规则和极大关联规则挖掘中相关核心概念的描述问题, 获得了二者的统一数学刻画. 实例分析表明, 与经典挖掘方法相比, 基于软集逻辑公式的极大关联规则挖掘方法能有效降低冗余, 并剔除无效规则, 提高了所得规则的准确性和挖掘效率.

关键词: 实现集, 软集, 关联规则, 逻辑公式, 数据挖掘

Abstract: Aiming at the problem that the partition of the item domain was not considered in the definition of regular association rules, we proposed that maximal association rules were useful complement to regular association rules. Using soft set theory and logical formulas on soft sets as the main tool, we solved the problem of the description of related core concepts for mining both regular and maximal association rules, and obtained unified mathematical characterization of these concepts. The example analysis shows that, compared with classical mining methods, maximal association rule mining method based on logical formulas on soft sets can effectively reduce redundancy and eliminate invalid rules, which improves the accuracy and mining efficiency of rule.

Key words: data mining, implementation set, association rule, logical formula, soft set

中图分类号: 

  • TP182