[1]顾伟[][],傅德胜[][],蔡玮[]. 基于命题逻辑的关联规则挖掘算法[J].计算机技术与发展,2015,25(03):91-94.
　GU Wei[][],FU De-sheng[][],CAI Wei[]. Association Rules Mining Algorithm Based on Propositional Logic[J].,2015,25(03):91-94.
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 基于命题逻辑的关联规则挖掘算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年03期
页码:
91-94
栏目:
智能、算法、系统工程
出版日期:
2015-03-10

文章信息/Info

Title:
 Association Rules Mining Algorithm Based on Propositional Logic
文章编号:
1673-629X（2015)03-0091-04
作者:
 顾伟[1][2];  傅德胜[1][2];  蔡玮[3]
 1.南京信息工程大学 江苏省网络监控中心；2.南京信息工程大学 计算机与软件学院；3.南京工程学院 计算机工程学院院；
Author(s):
 GU Wei[1][2];  FU De-sheng[1][2]; CAI Wei[3]
关键词:
 ; 数据挖掘; 关联规则; 命题逻辑; 关联性
Keywords:
 ; data mining; association rules; propositional logic; correlation
分类号:
TP311
文献标志码:
A
摘要:
 数据挖掘是从数据库中发现潜在有用知识或者感兴趣模式的过程。事务数据库中发现关联规则是最常见的数据挖掘，目的在于帮助市场决策者发现事务数据库中项目之间的关联性。对关联规则算法进行了研究，通过使用命题逻辑，在最小支持度值未能确定的情况下，直接推导项目之间的关系。该方法把关联规则和等价命题映射起来，形成一种对应关系。如果一个规则满足逻辑相等，那么该规则是一个相关关联规则。通过实例证明了文中提出的高度相关关联规则挖掘算法是有效的。实验也表明该挖掘算法比Apriori算法更有用。
Abstract:
 Data mining is the process found potentially useful knowledge or interest mode from the database. The association rules found in the transaction database is the most common data mining,which is intended to help decision makers of market find transaction database correlation between items. Association rules algorithm was studied by using propositional logic,in the case that minimum support value cannot be determined,directly derivate the relationship between the project. The association rules and equivalence proposition are mapped together in this way to form a corresponding relation. If a rule is satisfied logic are equal,the rule is a relevant association rules. Demon-strated by examples presented in this paper,the highly relevant association rule mining algorithm is effective. Experiments also show that the mining algorithm is more useful than Apriori algorithm.

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更新日期/Last Update: 2015-05-04