Mining high coherent association rules with consideration of support measure
作者：
Highlights：
• We propose a HCAR algorithm for mining high coherent association rules.
• The derived rules have the logical equivalence property.
• The derived rules are expected to be more reliable in terms of business.
• Lower and upper bounds of itemsets are defined for speeding up the process.
• Two datasets are used to show the proposed approach is effective.
摘要
•We propose a HCAR algorithm for mining high coherent association rules.•The derived rules have the logical equivalence property.•The derived rules are expected to be more reliable in terms of business.•Lower and upper bounds of itemsets are defined for speeding up the process.•Two datasets are used to show the proposed approach is effective.
论文关键词：Data mining,Association rules,Propositional logic,Coherent rules,Highly coherent rules
论文评审过程：Available online 12 June 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.06.002
