Implementation of coherent rule mining algorithm for association rule mining

被引：0

作者：

Davale, Aditya A. ^{[1
]}

Shende, Shailendra W. ^{[1
]}

机构：

[1] Yeshwantrao Chavan Coll Engn, Dept Informat Technol, Nagpur, Maharashtra, India

来源：

2015 1ST INTERNATIONAL CONFERENCE ON FUTURISTIC TRENDS ON COMPUTATIONAL ANALYSIS AND KNOWLEDGE MANAGEMENT (ABLAZE) | 2015年

关键词：

data mining; association rules; support;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In the data mining field, association rules are generated from domain knowledge which is evaluated from the minimum support threshold value. The accuracy in setting up this threshold directly influences the number and the quality of association rules discovered. The number of association rules discovered is large in numbers but still misses some interesting rules and the rule's quality. So, the solution to this is the use of propositional logic to generate the association rules to avoid loss of rules. Coherent rules are discovered from the propositional logic so it does not require the domain expert. The coherent rules are discovered without knowing the value of minimum threshold. So, there is no need of deciding the threshold value. The results are compared with results apriori algorithm.

引用

页码：538 / 541

页数：4

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