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» Exception Rules Mining Based on Negative Association Rules
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AIA
2007
13 years 9 months ago
Evaluating generalized association rules through objective measures
Generalized association rules are rules that contain some background knowledge, therefore, giving a more general view of the domain. This knowledge is codified by a taxonomy set ...
Veronica Oliveira de Carvalho, Solange Oliveira Re...
DATAMINE
2008
89views more  DATAMINE 2008»
13 years 7 months ago
Mining conjunctive sequential patterns
Abstract. In this paper we aim at extending the non-derivable condensed representation in frequent itemset mining to sequential pattern mining. We start by showing a negative examp...
Chedy Raïssi, Toon Calders, Pascal Poncelet
ICFCA
2007
Springer
14 years 1 months ago
A Parameterized Algorithm for Exploring Concept Lattices
Kuznetsov shows that Formal Concept Analysis (FCA) is a natural framework for learning from positive and negative examples. Indeed, the results of learning from positive examples (...
Peggy Cellier, Sébastien Ferré, Oliv...
DATAMINE
2006
131views more  DATAMINE 2006»
13 years 7 months ago
A systematic approach to the assessment of fuzzy association rules
In order to allow for the analysis of data sets including numerical attributes, several generalizations of association rule mining based on fuzzy sets have been proposed in the li...
Didier Dubois, Eyke Hüllermeier, Henri Prade
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
13 years 11 months ago
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Knowledge discovery in databases (KDD) is a process that can include steps like forming the data set, data transformations, discovery of patterns, searching for exceptions to a pat...
Jean-François Boulicaut, Mika Klemettinen, ...