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FUZZIEEE
2007
IEEE
15 years 9 months ago
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
Rafael Alcalá, Jesús Alcalá-F...
132
Voted
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 3 months ago
Weighted Association Rule Mining using weighted support and significance framework
We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
Feng Tao, Fionn Murtagh, Mohsen Farid
132
Voted
CIBCB
2005
IEEE
15 years 4 months ago
Neuro-fuzzy Prediction of Biological Activity and Rule Extraction for HIV-1 Protease Inhibitors
— A fuzzy neural network (FNN) and multiple linear regression (MLR) were used to predict biological activities of 26 newly designed HIV-1 protease potential inhibitory compounds....
Razvan Andonie, Levente Fabry-Asztalos, Catharine ...
105
Voted
CONTEXT
2003
Springer
15 years 7 months ago
On the Difference between Bridge Rules and Lifting Axioms
Abstract. In a previous paper, we proposed a first formal and conceptual comparison between the two most important formalizations of context in AI: Propositional Logic of Context ...
Paolo Bouquet, Luciano Serafini
163
Voted
KDD
1999
ACM
237views Data Mining» more  KDD 1999»
15 years 6 months ago
Using Association Rules for Product Assortment Decisions: A Case Study
It has been claimed that the discovery of association rules is well-suited for applications of market basket analysis to reveal regularities in the purchase behaviour of customers...
Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert We...