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» Mining Positive and Negative Fuzzy Association Rules
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DAWAK
2007
Springer
15 years 1 months ago
Extraction of Association Rules Based on Literalsets
In association rules mining, current trend is witnessing the emergence of a growing number of works toward bringing negative items to light in the mined knowledge. However, the amo...
Ghada Gasmi, Sadok Ben Yahia, Engelbert Mephu Ngui...
EUSFLAT
2007
103views Fuzzy Logic» more  EUSFLAT 2007»
14 years 11 months ago
Measuring Variation Strength in Gradual Dependencies
In this paper we extend a previous definition of gradual dependence as a special kind of (crisp) association rule, in order to measure not only the existence of a tendency, but i...
Carlos Molina, José-María Serrano, D...
BMCBI
2008
171views more  BMCBI 2008»
14 years 9 months ago
Fuzzy association rules for biological data analysis: A case study on yeast
Background: Last years' mapping of diverse genomes has generated huge amounts of biological data which are currently dispersed through many databases. Integration of the info...
Francisco J. Lopez, Armando Blanco, Fernando Garci...
ADMA
2010
Springer
248views Data Mining» more  ADMA 2010»
14 years 7 months ago
Classification Inductive Rule Learning with Negated Features
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...
Stephanie Chua, Frans Coenen, Grant Malcolm
115
Voted
IDA
2002
Springer
14 years 9 months ago
Optimization of association rule mining queries
Levelwise algorithms (e.g., the Apriori algorithm) have been proved eective for association rule mining from sparse data. However, in many practical applications, the computation ...
Baptiste Jeudy, Jean-François Boulicaut