Fabrice E. Guillet
Fabrice E. Guillet
Full Professor, Computer Science, LS2N CNRS UMR6004, University of Nantes, Polytech Nantes
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Cited by
Cited by
Quality Measures in Data Mining
F Guillet, HJ Hamilton
Studies in Computational Intelligence, Springer, 2007
Statistical Implicative Analysis: theory and applications
R Gras, E Suzuki, F Guillet, F Spagnolo
Springer Verlag, 2008
Knowledge-based interactive postmining of association rules using ontologies
C Marinica, F Guillet
IEEE Transactions on knowledge and data engineering 22 (6), 784-797, 2010
Association rule ontology matching approach
J David
International Journal on Semantic Web and Information Systems (IJSWIS) 3 (2 …, 2007
Using information-theoretic measures to assess association rule interestingness
J Blanchard, F Guillet, R Gras, H Briand
Fifth IEEE International Conference on Data Mining (ICDM'05), 8 pp., 2005
Analyse Statistique Implicative: Une méthode d’analyse de données pour la recherche de causalités
R Gras, JC Régnier, F Guillet
Revue national des Technologies de l'Information (RNTI), 2009
Matching directories and OWL ontologies with AROMA
J David, F Guillet, H Briand
Proceedings of the 15th ACM international conference on Information and …, 2006
Une version entropique de l'intensité d'implication pour les corpus volumineux
R Gras, P Kuntz, R Couturier, F Guillet
Interactive visual exploration of association rules with rule-focusing methodology
J Blanchard, F Guillet, H Briand
Knowledge and Information Systems 13 (1), 43-75, 2007
Assessing rule interestingness with a probabilistic measure of deviation from equilibrium
J Blanchard, F Guillet, H Briand, R Gras
11th international symposium on Applied Stochastic Models and Data Analysis …, 2005
A user-driven and quality-oriented visualization for mining association rules
J Blanchard, F Guillet, H Briand
Third IEEE International Conference on Data Mining, 493-496, 2003
Exploratory visualization for association rule rummaging
J Blanchard, F Guillet, H Briand
KDD-03 workshop on multimedia data mining (MDM-03) 3, 2003
L'analyse statistique implicative Méthode exploratoire et confirmatoire à la recherche de causalités
R Gras, JC Régnier, C Marinica, F Guillet
Cépaduès Editions, 2013
Post-processing of discovered association rules using ontologies
C Marinica, F Guillet, H Briand
2008 IEEE International Conference on Data Mining Workshops, 126-133, 2008
Improving the discovery of association rules with intensity of implication
S Guillaume, F Guillet, J Philippe
European Symposium on Principles of Data Mining and Knowledge Discovery, 318-327, 1998
Implication Intensity: From the Basic Statistical Definition to the Entropic Version Polytechnique de l’Universite de Nantes, France
J Blanchard, P Kuntz, F Guillet, RG Ecole
Statistical data mining and knowledge discovery, 505-518, 2003
A user-driven process for mining association rules
P Kuntz, F Guillet, R Lehn, H Briand
European Conference on Principles of Data Mining and Knowledge Discovery …, 2000
A graph-based clustering approach to evaluate interestingness measures: a tool and a comparative study
XH Huynh, F Guillet, J Blanchard, P Kuntz, H Briand, R Gras
Quality measures in data mining, 25-50, 2007
Visual analytics for exploring topic long-term evolution and detecting weak signals in company targeted tweets
L Pépin, P Kuntz, J Blanchard, F Guillet, P Suignard
Computers & Industrial Engineering 112, 450-458, 2017
ARQAT: an exploratory analysis tool for interestingness measures
XH Huynh, F Guillet, H Briand
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