Jean-Francois Boulicaut
Jean-Francois Boulicaut
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Free-sets: a condensed representation of boolean data for the approximation of frequency queries
JF Boulicaut, A Bykowski, C Rigotti
Data Mining and Knowledge Discovery 7 (1), 5-22, 2003
Strong-association-rule mining for large-scale gene-expression data analysis: a case study on human SAGE data
C Becquet, S Blachon, B Jeudy, JF Boulicaut, O Gandrillon
Genome Biology 3, 1-16, 2002
Approximation of frequency queries by means of free-sets
JF Boulicaut, A Bykowski, C Rigotti
PKDD 2000, 24-43, 2000
A survey on condensed representations for frequent sets
T Calders, C Rigotti, JF Boulicaut
Constraint-Based Mining and Inductive Databases: European Workshop on …, 2006
Closed patterns meet n-ary relations
L Cerf, J Besson, C Robardet, JF Boulicaut
ACM Transactions on Knowledge Discovery from Data 3 (1), 1-30, 2009
Frequent closures as a concise representation for binary data mining
JF Boulicaut, A Bykowski
PAKDD 2000, 62-73, 2000
Using queries to improve database reverse engineering
JM Petit, J Kouloumdjian, JF Boulicaut, F Toumani
ER 1994, 369-386, 1994
Constraint-based concept mining and its application to microarray data analysis
J Besson, C Robardet, JF Boulicaut, S Rome
Intelligent Data Analysis 9 (1), 59-82, 2005
Towards the reverse engineering of renormalized relational databases
JM Petit, F Toumani, JF Boulicaut, J Kouloumdjian
IEEE ICDE 1996, 218-227, 1996
Constraint-based data mining
JF Boulicaut, B Jeudy
Data mining and knowledge discovery handbook, 339-354, 2010
Mining graph topological patterns: Finding co-variations among vertex descriptors
A Prado, M Plantevit, C Robardet, JF Boulicaut
IEEE Transactions on Knowledge and Data Engineering 25 (9), 2090-2104, 2013
Data-Peeler: Constraint-based closed pattern mining in n-ary relations
L Cerf, J Besson, C Robardet, JF Boulicaut
SIAM DM 2008, 37-48, 2008
Modeling KDD processes within the inductive database framework
JF Boulicaut, M Klemettinen, H Mannila
DaWaK 1999, 293-302, 1999
Constrained co-clustering of gene expression data
RG Pensa, JF Boulicaut
SIAM DM 2008, 25–36, 2008
Assessment of discretization techniques for relevant pattern discovery from gene expression data
RG Pensa, C Leschi, J Besson, JF Boulicaut
ACM BIOKDD co-located with KDD 2004, 24–30, 2004
Using transposition for pattern discovery from microarray data
F Rioult, JF Boulicaut, B Crémilleux, J Besson
ACM SIGMOD workshop DMKD, 73-79, 2003
Towards the tractable discovery of association rules with negations
JF Boulicaut, A Bykowski, B Jeudy
FQAS 2000, 425-434, 2000
Mining a new fault-tolerant pattern type as an alternative to formal concept discovery
J Besson, C Robardet, JF Boulicaut
ICCS 2006, 144-157, 2006
Anytime discovery of a diverse set of patterns with Monte Carlo tree search
G Bosc, JF Boulicaut, C Raïssi, M Kaytoue
Data Mining and Knowledge Discovery 32 (3), 604-650, 2018
Cohesive co-evolution patterns in dynamic attributed graphs
E Desmier, M Plantevit, C Robardet, JF Boulicaut
DS 2012, 110-124, 2012
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