Hierarchical interestingness measures for association rules with generalization on both antecedent and consequent sides
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- 作者：Fernando Benites ; Fernando.Benites@uni.kn" class="auth_mail" title="E-mail the corresponding author ; Elena Sapozhnikova Elena.Sapozhnikova@uni.kn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Data Mining ; Association rules ; Cross-ontology rules ; Interestingness measures ; Ontology matching
- 刊名：Pattern Recognition Letters
- 出版年：2015
- 出版时间：1 November 2015
- 年：2015
- 卷：65
- 期：Complete
- 页码：197-203
- 全文大小：402 K
文摘
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Hierarchical interesting measures for generalized association rules are studied.
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An extension of such measures to generalization on both sides of a rule is proposed.
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Two of three extended hierarchical measures found more true rules in the experiments.