An Approach to Association Rules Mining Using Inclusion Degree of Soft Sets

GENG Sheng-ling; LI Yong-ming; LIU Zhen

doi:10.3969/j.issn.0372-2112.2013.04.030

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An Approach to Association Rules Mining Using Inclusion Degree of Soft Sets

更新时间：2025-07-16

- An Approach to Association Rules Mining Using Inclusion Degree of Soft Sets
- Acta Electronica Sinica Vol. 41, Issue 4, Pages: 804-809(2013)
- 作者机构：
  
  1. 陕西师范大学计算机科学学院,陕西,西安,710069
  2. 青海师范大学计算机学院,青海,西宁,810008
  3. 日本长崎综合科技大学,长崎,日本,851-0193
  4. 陕西师范大学计算机科学学院陕西西安,710069
  5. 青海师范大学计算机学院青海西宁,810008
  6. 日本长崎综合科技大学日本长崎,851-0193
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2013.04.030
  CLC： TP391
- Published：2013
- 稿件说明：
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GENG Sheng-ling, LI Yong-ming, LIU Zhen. An Approach to Association Rules Mining Using Inclusion Degree of Soft Sets[J]. Acta Electronica Sinica, 2013, 41(4): 804-809.
DOI：

GENG Sheng-ling, LI Yong-ming, LIU Zhen. An Approach to Association Rules Mining Using Inclusion Degree of Soft Sets[J]. Acta Electronica Sinica, 2013, 41(4): 804-809. DOI： 10.3969/j.issn.0372-2112.2013.04.030.

摘要

本文在深入研究软集数据分析的基础上

将包含度引入软集数据关联规则挖掘中

利用包含度理论描述属性集之间的量化关系

给出软集上属性集间的包含度、关联规则和最大关联规则的概念

讨论包含度和可信度之间的联系.在此基础上给出利用包含度在事务数据软集中挖掘满足给定的支持度和可信度阈值的软关联规则方法

以及最大软关联规则的提取算法.理论证明和实例分析表明该关联规则挖掘方法是有效的

并通过实验对算法的性能进行了比较.

Abstract

This paper aims to present an approach for mining regular association rules and maximal association rules using soft set and inclusion degree theory from transactional datasets.We first give the notions of inclusion degree

association rule and maximum association rules between attribute sets of soft set.Then we discuss the relationship between inclusion degree and confidence.Furthermore

we give an algorithm of soft maximal association rules mining using inclusion degree of soft set.The experiments show the algorithm improves greatly the performance of maximal association rules mining.

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