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ORCIDJean-François Boulicaut
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- affiliation: LIRS Lyon, France
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2020 – today
- 2021
[j21]Romain Mathonat
, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue:
Anytime mining of sequential discriminative patterns in labeled sequences. Knowl. Inf. Syst. 63(2): 439-476 (2021)- [c114]Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue:
Anytime Subgroup Discovery in High Dimensional Numerical Data. DSAA 2021: 1-10 - [c113]Alexandre Millot, Rémy Cazabet, Jean-François Boulicaut:
Exceptional Model Mining meets Multi-objective Optimization. SDM 2021: 378-386 - 2020
- [j20]Frédéric Flouvat, Nazha Selmaoui-Folcher, Jérémy Sanhes, Chengcheng Mu, Claude Pasquier, Jean-François Boulicaut:
Mining evolutions of complex spatial objects using a single-attributed Directed Acyclic Graph. Knowl. Inf. Syst. 62(10): 3931-3971 (2020) - [c112]Romain Mathonat, Jean-François Boulicaut, Mehdi Kaytoue:
A Behavioral Pattern Mining Approach to Model Player Skills in Rocket League. CoG 2020: 267-274 - [c111]Alexandre Millot, Rémy Cazabet, Jean-François Boulicaut:
Découverte d'un sous-groupe optimal dans des données purement numériques. EGC 2020: 25-36 - [c110]Alexandre Millot, Romain Mathonat, Rémy Cazabet, Jean-François Boulicaut:
Actionable Subgroup Discovery and Urban Farm Optimization. IDA 2020: 339-351 - [c109]Alexandre Millot, Rémy Cazabet, Jean-François Boulicaut:
Optimal Subgroup Discovery in Purely Numerical Data. PAKDD (2) 2020: 112-124
2010 – 2019
- 2019
- [c108]Romain Mathonat, Diana Nurbakova, Jean-François Boulicaut, Mehdi Kaytoue:
SeqScout: Using a Bandit Model to Discover Interesting Subgroups in Labeled Sequences. DSAA 2019: 81-90 - [c107]Romain Mathonat, Jean-François Boulicaut, Mehdi Kaytoue:
Découverte de sous-groupes à partir de données séquentielles par échantillonnage et optimisation locale. EGC 2019: 153-164 - 2018
- [j19]Guillaume Bosc, Jean-François Boulicaut, Chedy Raïssi, Mehdi Kaytoue:
Anytime discovery of a diverse set of patterns with Monte Carlo tree search. Data Min. Knowl. Discov. 32(3): 604-650 (2018) - 2017
- [j18]Guillaume Bosc, Philip Tan, Jean-François Boulicaut, Chedy Raïssi, Mehdi Kaytoue:
A Pattern Mining Approach to Study Strategy Balance in RTS Games. IEEE Trans. Comput. Intell. AI Games 9(2): 123-132 (2017) - [c106]Guillaume Bosc, Jean-François Boulicaut, Chedy Raïssi, Mehdi Kaytoue:
Découverte de sous-groupes avec les arbres de recherche de Monte Carlo. EGC 2017: 273-284 - [c105]Víctor Codocedo, Guillaume Bosc, Mehdi Kaytoue, Jean-François Boulicaut, Amedeo Napoli:
A Proposition for Sequence Mining Using Pattern Structures. ICFCA 2017: 106-121 - 2016
- [c104]Jean-François Boulicaut, Marc Plantevit, Céline Robardet:
Local Pattern Detection in Attributed Graphs. Solving Large Scale Learning Tasks 2016: 168-183 - [c103]Guillaume Bosc, Jérôme Golebiowski, Moustafa Bensafi, Céline Robardet, Marc Plantevit, Jean-François Boulicaut, Mehdi Kaytoue:
Local Subgroup Discovery for Eliciting and Understanding New Structure-Odor Relationships. DS 2016: 19-34 - [c102]Olivier Cavadenti, Víctor Codocedo, Jean-François Boulicaut, Mehdi Kaytoue:
What Did I Do Wrong in My MOBA Game? Mining Patterns Discriminating Deviant Behaviours. DSAA 2016: 662-671 - [c101]Olivier Cavadenti, Víctor Codocedo, Mehdi Kaytoue, Jean-François Boulicaut:
Découverte de motifs intelligibles et caractéristiques d'anomalies dans les traces unitaires. EGC 2016: 27-38 - [c100]Guillaume Bosc, Marc Plantevit, Jean-François Boulicaut, Moustafa Bensafi, Mehdi Kaytoue:
h(odor): Interactive Discovery of Hypotheses on the Structure-Odor Relationship in Neuroscience. ECML/PKDD (3) 2016: 17-21 - [i6]Guillaume Bosc, Chedy Raïssi, Jean-François Boulicaut, Mehdi Kaytoue:
Any-time Diverse Subgroup Discovery with Monte Carlo Tree Search. CoRR abs/1609.08827 (2016) - 2015
- [j17]Günce Keziban Orman, Vincent Labatut, Marc Plantevit, Jean-François Boulicaut:
Interpreting communities based on the evolution of a dynamic attributed network. Soc. Netw. Anal. Min. 5(1): 20:1-20:22 (2015) - [c99]Olivier Cavadenti, Víctor Codocedo, Jean-François Boulicaut, Mehdi Kaytoue:
When cyberathletes conceal their game: Clustering confusion matrices to identify avatar aliases. DSAA 2015: 1-10 - [c98]Nazha Selmaoui-Folcher, Frédéric Flouvat, Chengcheng Mu, Jérémy Sanhes, Jean-François Boulicaut:
Extraction complète efficace de chemins pondérés dans un a-DAG. EGC 2015: 179-190 - [c97]Guillaume Bosc, Mehdi Kaytoue, Marc Plantevit, Fabien De Marchi, Moustafa Bensafi, Jean-François Boulicaut:
Vers la découverte de modèles exceptionnels locaux : des règles descriptives liant les molécules à leurs odeurs. EGC 2015: 305-316 - [c96]Albrecht Zimmermann, Mehdi Kaytoue, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Profiling Users of the Velo'v Bike Sharing System. MUD@ICML 2015: 63-64 - [c95]Olivier Cavadenti, Víctor Codocedo, Mehdi Kaytoue, Jean-François Boulicaut:
Identifying Avatar Aliases in StarCraft 2. MLSA@PKDD/ECML 2015: 28-35 - [i5]Günce Keziban Orman, Vincent Labatut, Marc Plantevit, Jean-François Boulicaut:
Interpreting communities based on the evolution of a dynamic attributed network. CoRR abs/1506.04693 (2015) - [i4]Olivier Cavadenti, Víctor Codocedo, Jean-François Boulicaut, Mehdi Kaytoue:
Identifying Avatar Aliases in Starcraft 2. CoRR abs/1508.00801 (2015) - 2014
- [c94]Günce Keziban Orman, Vincent Labatut, Marc Plantevit, Jean-François Boulicaut:
A method for characterizing communities in dynamic attributed complex networks. ASONAM 2014: 481-484 - [c93]Frédéric Flouvat, Jérémy Sanhes, Claude Pasquier, Nazha Selmaoui-Folcher, Jean-François Boulicaut:
Improving pattern discovery relevancy by deriving constraints from expert models. ECAI 2014: 327-332 - [c92]Guillaume Bosc, Mehdi Kaytoue-Uberall, Chedy Raïssi, Jean-François Boulicaut, Philip Tan:
Mining Balanced Sequential Patterns in RTS Games. ECAI 2014: 975-976 - [c91]Günce Keziban Orman, Vincent Labatut, Marc Plantevit, Jean-François Boulicaut:
Une méthode pour caractériser les communautés des réseaux dynamiques à attributs. EGC 2014: 101-112 - [c90]Guillaume Bosc, Mehdi Kaytoue-Uberall, Chedy Raïssi, Jean-François Boulicaut:
Fouille de motifs séquentiels pour l'élicitation de stratégies à partir de traces d'interactions entre agents en compétition. EGC 2014: 359-370 - [c89]Elise Desmier, Marc Plantevit, Jean-François Boulicaut:
Granularité des motifs de co-variations dans des graphes attribués dynamiques. EGC 2014: 431-442 - [c88]Elise Desmier, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Granularity of Co-evolution Patterns in Dynamic Attributed Graphs. IDA 2014: 84-95 - [i3]Günce Keziban Orman, Vincent Labatut, Marc Plantevit, Jean-François Boulicaut:
A Method for Characterizing Communities in Dynamic Attributed Complex Networks. CoRR abs/1406.6597 (2014) - 2013
- [j16]Loïc Cerf, Jérémy Besson, Kim-Ngan Nguyen, Jean-François Boulicaut:
Closed and noise-tolerant patterns in n-ary relations. Data Min. Knowl. Discov. 26(3): 574-619 (2013) - [j15]Loïc Cerf, Dominique Gay, Nazha Selmaoui-Folcher, Bruno Crémilleux, Jean-François Boulicaut:
Parameter-free classification in multi-class imbalanced data sets. Data Knowl. Eng. 87: 109-129 (2013) - [j14]Kim-Ngan Nguyen, Loïc Cerf, Marc Plantevit, Jean-François Boulicaut:
Discovering descriptive rules in relational dynamic graphs. Intell. Data Anal. 17(1): 49-69 (2013) - [j13]Adriana Prado, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Mining Graph Topological Patterns: Finding Covariations among Vertex Descriptors. IEEE Trans. Knowl. Data Eng. 25(9): 2090-2104 (2013) - [c87]Jérémy Sanhes, Frédéric Flouvat, Claude Pasquier, Nazha Selmaoui-Folcher, Jean-François Boulicaut:
Extraction de motifs condensés dans un unique graphe orienté acyclique attribué. EGC 2013: 205-216 - [c86]Jérémy Sanhes, Frédéric Flouvat, Claude Pasquier, Nazha Selmaoui-Folcher, Jean-François Boulicaut:
Weighted Path as a Condensed Pattern in a Single Attributed DAG. IJCAI 2013: 1642-1648 - [c85]Guillaume Bosc, Mehdi Kaytoue, Chedy Raïssi, Jean-François Boulicaut:
Strategic Patterns Discovery in RTS-games for E-Sport with Sequential Pattern Mining. MLSA@PKDD/ECML 2013: 11-20 - [c84]Elise Desmier, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Trend Mining in Dynamic Attributed Graphs. ECML/PKDD (1) 2013: 654-669 - [i2]Günce Keziban Orman, Vincent Labatut, Marc Plantevit, Jean-François Boulicaut:
Une méthode pour caractériser les communautés des réseaux dynamiques à attributs. CoRR abs/1312.4676 (2013) - 2012
- [j12]Dominique Gay, Nazha Selmaoui-Folcher, Jean-François Boulicaut:
Application-independent feature construction based on almost-closedness properties. Knowl. Inf. Syst. 30(1): 87-111 (2012) - [c83]Elise Desmier, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Cohesive Co-evolution Patterns in Dynamic Attributed Graphs. Discovery Science 2012: 110-124 - [c82]Adriana Prado, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Extraction de co-variations entre des propriétés de sommets et leur position topologique dans un graphe attribué. EGC 2012: 267-278 - [c81]Jérémy Sanhes, Frédéric Flouvat, Nazha Selmaoui-Folcher, Jean-François Boulicaut:
Extraction d'arbres spatio-temporels d'itemsets pour le suivi environnemental. EGC 2012: 581-582 - [c80]Julien Salotti, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Supporting the Discovery of Relevant Topological Patterns in Attributed Graphs. ICDM Workshops 2012: 898-901 - [c79]Kim-Ngan Nguyen, Marc Plantevit, Jean-François Boulicaut:
Mining Disjunctive Rules in Dynamic Graphs. RIVF 2012: 1-6 - 2011
- [c78]Pierre-Nicolas Mougel, Marc Plantevit, Christophe Rigotti, Olivier Gandrillon, Jean-François Boulicaut:
Extraction sous contraintes d'ensembles de cliques homogènes. EGC 2011: 443-454 - [c77]Kim-Ngan Nguyen, Loïc Cerf, Marc Plantevit, Jean-François Boulicaut:
Multidimensional Association Rules in Boolean Tensors. SDM 2011: 570-581 - 2010
- [j11]Ruggero G. Pensa, Jean-François Boulicaut, Francesca Cordero, Maurizio Atzori:
Co-clustering numerical data under user-defined constraints. Stat. Anal. Data Min. 3(1): 38-55 (2010) - [c76]Jérémy Besson, Ieva Mitasiunaite, Audrone Lupeikiene, Jean-François Boulicaut:
Comparing Intended and Real Usage in Web Portal: Temporal Logic and Data Mining. BIS 2010: 83-93 - [c75]Kim-Ngan Nguyen, Loïc Cerf, Marc Plantevit, Jean-François Boulicaut:
Discovering Inter-Dimensional Rules in Dynamic Graphs. NyNaK 2010 - [p9]Jérémy Besson, Jean-François Boulicaut, Tias Guns, Siegfried Nijssen:
Generalizing Itemset Mining in a Constraint Programming Setting. Inductive Databases and Constraint-Based Data Mining 2010: 107-126 - [p8]Loïc Cerf, Tran Bao Nhan Nguyen, Jean-François Boulicaut:
Mining Constrained Cross-Graph Cliques in Dynamic Networks. Inductive Databases and Constraint-Based Data Mining 2010: 199-228 - [p7]Christophe Rigotti, Ieva Mitasiunaite, Jérémy Besson, Laurène Meyniel, Jean-François Boulicaut, Olivier Gandrillon:
Using a Solver Over the String Pattern Domain to Analyze Gene Promoter Sequences. Inductive Databases and Constraint-Based Data Mining 2010: 407-423 - [p6]Jean-François Boulicaut, Baptiste Jeudy:
Constraint-based Data Mining. Data Mining and Knowledge Discovery Handbook 2010: 339-354 - [p5]Jean-François Boulicaut, Cyrille Masson:
Data Mining Query Languages. Data Mining and Knowledge Discovery Handbook 2010: 655-664
2000 – 2009
- 2009
- [j10]Ieva Mitasiunaite, Christophe Rigotti, Stéphane Schicklin, Laurène Meyniel, Jean-François Boulicaut, Olivier Gandrillon:
Extracting Signature Motifs from Promoter Sets of Differentially Expressed Genes. Silico Biol. 9(1-2): S17-S39 (2009) - [j9]Loïc Cerf, Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
Closed patterns meet n-ary relations. ACM Trans. Knowl. Discov. Data 3(1): 3:1-3:36 (2009) - [c74]Loïc Cerf, Pierre-Nicolas Mougel, Jean-François Boulicaut:
Agglomerating local patterns hierarchically with ALPHA. CIKM 2009: 1753-1756 - [c73]Nazha Selmaoui, Dominique Gay, Jean-François Boulicaut:
Construction de descripteurs pour classer à partir d'exemples bruités. EGC 2009: 91-102 - [c72]Loïc Cerf, Jérémy Besson, Jean-François Boulicaut:
Extraction de motifs fermés dans des relations n-aires bruitées. EGC 2009: 163-168 - [c71]Loïc Cerf, Tran Bao Nhan Nguyen, Jean-François Boulicaut:
Discovering Relevant Cross-Graph Cliques in Dynamic Networks. ISMIS 2009: 513-522 - [c70]Dominique Gay, Nazha Selmaoui, Jean-François Boulicaut:
Application-Independent Feature Construction from Noisy Samples. PAKDD 2009: 965-972 - [e9]Niall M. Adams, Céline Robardet, Arno Siebes, Jean-François Boulicaut:
Advances in Intelligent Data Analysis VIII, 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009. Proceedings. Lecture Notes in Computer Science 5772, Springer 2009, ISBN 978-3-642-03914-0 [contents] - 2008
- [j8]Johan Leyritz, Stéphane Schicklin, Sylvain Blachon, Céline Keime, Céline Robardet, Jean-François Boulicaut, Jérémy Besson, Ruggero G. Pensa, Olivier Gandrillon:
SQUAT: A web tool to mine human, murine and avian SAGE data. BMC Bioinform. 9 (2008) - [c69]Loïc Cerf, Dominique Gay, Nazha Selmaoui, Jean-François Boulicaut:
A Parameter-Free Associative Classification Method. DaWaK 2008: 293-304 - [c68]Ruggero G. Pensa, Jean-François Boulicaut:
Co-classification sous contraintes par la somme des résidus quadratiques. EGC 2008: 655-666 - [c67]Jérémy Besson, Christophe Rigotti, Ieva Mitasiunaite, Jean-François Boulicaut:
Parameter Tuning for Differential Mining of String Patterns. ICDM Workshops 2008: 77-86 - [c66]Jean-François Boulicaut:
If Constraint-Based Mining is the Answer: What is the Constraint? (Invited Talk). ICDM Workshops 2008: 730 - [c65]Jean-François Boulicaut, Jérémy Besson:
Actionability and Formal Concepts: A Data Mining Perspective. ICFCA 2008: 14-31 - [c64]Dominique Gay, Nazha Selmaoui, Jean-François Boulicaut:
Feature Construction Based on Closedness Properties Is Not That Simple. PAKDD 2008: 112-123 - [c63]Ruggero G. Pensa, Jean-François Boulicaut:
Constrained Co-clustering of Gene Expression Data. SDM 2008: 25-36 - [c62]Loïc Cerf, Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
Data Peeler: Contraint-Based Closed Pattern Mining in n-ary Relations. SDM 2008: 37-48 - [c61]Ruggero G. Pensa, Jean-François Boulicaut:
Numerical Data Co-clustering via Sum-Squared Residue Minimization and User-defined Constraint Satisfaction. SEBD 2008: 279-286 - [e8]Jean-François Boulicaut, Michael R. Berthold, Tamás Horváth:
Discovery Science, 11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008. Proceedings. Lecture Notes in Computer Science 5255, Springer 2008, ISBN 978-3-540-88410-1 [contents] - 2007
- [j7]Sylvain Blachon, Ruggero G. Pensa, Jérémy Besson, Céline Robardet, Jean-François Boulicaut, Olivier Gandrillon:
Clustering Formal Concepts to Discover Biologically Relevant Knowledge from Gene Expression Data. Silico Biol. 7(4-5): 467-483 (2007) - [c60]Dominique Gay, Nazha Selmaoui, Jean-François Boulicaut:
Pattern-based decision tree construction. ICDIM 2007: 291-296 - 2006
- [j6]Ruggero G. Pensa, Céline Robardet, Jean-François Boulicaut:
Supporting bi-cluster interpretation in 0/1 data by means of local patterns. Intell. Data Anal. 10(5): 457-472 (2006) - [c59]Ieva Mitasiunaite, Jean-François Boulicaut:
Introducing Softness into Inductive Queries on String Databases. DB&IS 2006: 117-130 - [c58]Nazha Selmaoui, Claire Leschi, Dominique Gay, Jean-François Boulicaut:
Feature Construction and delta-Free Sets in 0/1 Samples. Discovery Science 2006: 363-367 - [c57]Clément Fauré, Sylvie Delprat, Jean-François Boulicaut, Alain Mille:
Iterative Bayesian Network Implementation by Using Annotated Association Rules. EKAW 2006: 326-333 - [c56]Clément Fauré, Sylvie Delprat, Alain Mille, Jean-François Boulicaut:
Utilisation des réseaux bayésiens dans le cadre de l'extraction de règles d'association. EGC 2006: 569-580 - [c55]Hunor Albert-Lorincz, Jean-François Boulicaut:
Amélioration des indicateurs techniques pour l'analyse du marché financier. EGC 2006: 693-704 - [c54]Clément Fauré, Sylvie Delprat, Alain Mille, Jean-François Boulicaut:
Construction itérative d'un modèle de connaissance par l'exploitation de règles d'association. Actes d'IC 2006: 1-10 - [c53]Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
Mining a New Fault-Tolerant Pattern Type as an Alternative to Formal Concept Discovery. ICCS 2006: 144-157 - [c52]Ruggero G. Pensa, Céline Robardet, Jean-François Boulicaut:
Towards Constrained Co-clustering in Ordered 0/1 Data Sets. ISMIS 2006: 425-434 - [c51]Jérémy Besson, Céline Robardet, Luc De Raedt, Jean-François Boulicaut:
Mining Bi-sets in Numerical Data. KDID 2006: 11-23 - [c50]Ieva Mitasiunaite, Jean-François Boulicaut:
Looking for monotonicity properties of a similarity constraint on sequences. SAC 2006: 546-552 - [e7]Francesco Bonchi, Jean-François Boulicaut:
Knowledge Discovery in Inductive Databases, 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers. Lecture Notes in Computer Science 3933, Springer 2006, ISBN 3-540-33292-8 [contents] - 2005
- [j5]Jérémy Besson, Céline Robardet, Jean-François Boulicaut, Sophie Rome:
Constraint-based concept mining and its application to microarray data analysis. Intell. Data Anal. 9(1): 59-82 (2005) - [c49]Ruggero G. Pensa, Jean-François Boulicaut:
Towards Fault-Tolerant Formal Concept Analysis. AI*IA 2005: 212-223 - [c48]Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
Approximation de collections de concepts formels par des bi-ensembles denses et pertinents. CAP 2005: 313-328 - [c47]Ruggero G. Pensa, Jean-François Boulicaut:
From Local Pattern Mining to Relevant Bi-cluster Characterization. IDA 2005: 293-304 - [c46]Jérémy Besson, Ruggero G. Pensa, Céline Robardet, Jean-François Boulicaut:
Constraint-Based Mining of Fault-Tolerant Patterns from Boolean Data. KDID 2005: 55-71 - [c45]Ruggero G. Pensa, Céline Robardet, Jean-François Boulicaut:
A Bi-clustering Framework for Categorical Data. PKDD 2005: 643-650 - [p4]Jean-François Boulicaut, Baptiste Jeudy:
Constraint-Based Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 399-416 - [p3]Jean-François Boulicaut, Cyrille Masson:
Data Mining Query Languages. The Data Mining and Knowledge Discovery Handbook 2005: 715-727 - [e6]Jean-François Boulicaut, Luc De Raedt, Heikki Mannila:
Constraint-Based Mining and Inductive Databases, European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers. Lecture Notes in Computer Science 3848, Springer 2005, ISBN 3-540-31331-1 [contents] - [e5]Katharina Morik, Jean-François Boulicaut, Arno Siebes:
Local Pattern Detection, International Seminar, Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers. Lecture Notes in Computer Science 3539, Springer 2005, ISBN 3-540-26543-0 [contents] - 2004
- [j4]Jean-François Boulicaut, Bruno Crémilleux:
Introduction. Ingénierie des Systèmes d Inf. 9(3-4): 7-22 (2004) - [c44]Toon Calders, Christophe Rigotti, Jean-François Boulicaut:
A Survey on Condensed Representations for Frequent Sets. Constraint-Based Mining and Inductive Databases 2004: 64-80 - [c43]Ruggero G. Pensa, Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining. Constraint-Based Mining and Inductive Databases 2004: 328-347 - [c42]Ruggero G. Pensa, Jean-François Boulicaut:
Boolean Property Encoding for Local Set Pattern Discovery: An Application to Gene Expression Data Analysis. Local Pattern Detection 2004: 115-134 - [c41]Ruggero G. Pensa, Jérémy Besson, Jean-François Boulicaut:
A Methodology for Biologically Relevant Pattern Discovery from Gene Expression Data. Discovery Science 2004: 230-241 - [c40]Ruggero G. Pensa, Claire Leschi, Jérémy Besson, Jean-François Boulicaut:
Assessment of discretization techniques for relevant pattern discovery from gene expression data. BIOKDD 2004: 24-30 - [c39]Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Data. KDID 2004: 33-45 - [c38]Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
Constraint-Based Mining of Formal Concepts in Transactional Data. PAKDD 2004: 615-624 - [c37]Céline Robardet, Ruggero G. Pensa, Jérémy Besson, Jean-François Boulicaut:
Using Classification and Visualization on Pattern Databases for Gene Expression Data Analysis. PaRMa 2004 - [c36]Cyrille Masson, Céline Robardet, Jean-François Boulicaut:
Optimizing subset queries: a step towards SQL-based inductive databases for itemsets. SAC 2004: 535-539 - [p2]Jean-François Boulicaut:
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach. Database Support for Data Mining Applications 2004: 1-23 - [p1]Marco Botta, Jean-François Boulicaut, Cyrille Masson, Rosa Meo:
Query Languages Supporting Descriptive Rule Mining: A Comparative Study. Database Support for Data Mining Applications 2004: 24-51 - [e4]Jean-François Boulicaut, Katharina Morik, Arno Siebes:
Detecting Local Patterns, 12.04. - 16.04.2004. Dagstuhl Seminar Proceedings 04161, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2004 [contents] - [e3]Jean-François Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi:
Machine Learning: ECML 2004, 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004, Proceedings. Lecture Notes in Computer Science 3201, Springer 2004, ISBN 3-540-23105-6 [contents] - [e2]Jean-François Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi:
Knowledge Discovery in Databases: PKDD 2004, 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Pisa, Italy, September 20-24, 2004, Proceedings. Lecture Notes in Computer Science 3202, Springer 2004, ISBN 3-540-23108-0 [contents] - [i1]Jean-François Boulicaut, Katharina Morik, Arno Siebes:
04161 Abstracts Collection - Detecting Local Patterns. Detecting Local Patterns 2004 - 2003
- [j3]Jean-François Boulicaut, Artur Bykowski, Christophe Rigotti:
Free-Sets: A Condensed Representation of Boolean Data for the Approximation of Frequency Queries. Data Min. Knowl. Discov. 7(1): 5-22 (2003) - [c35]Kimmo Hätönen, Jean-François Boulicaut, Mika Klemettinen, Markus Miettinen, Cyrille Masson:
Comprehensive Log Compression with Frequent Patterns. DaWaK 2003: 360-370 - [c34]François Rioult, Jean-François Boulicaut, Bruno Crémilleux, Jérémy Besson:
Using transposition for pattern discovery from microarray data. DMKD 2003: 73-79 - [c33]Hunor Albert-Lorincz, Jean-François Boulicaut:
A Framework for Frequent Sequence Mining under Generalized Regular Expression Constraints. KDID 2003: 2-16 - [c32]François Rioult, Céline Robardet, Sylvain Blachon, Bruno Crémilleux, Olivier Gandrillon, Jean-François Boulicaut:
Mining Concepts from Large SAGE Gene Expression Matrices. KDID 2003: 107-118 - [c31]Marion Leleu, Christophe Rigotti, Jean-François Boulicaut, Guillaume Euvrard:
GO-SPADE: Mining Sequential Patterns over Datasets with Consecutive Repetitions. MLDM 2003: 293-306 - [c30]Marion Leleu, Christophe Rigotti, Jean-François Boulicaut, Guillaume Euvrard:
Constraint-Based Mining of Sequential Patterns over Datasets with Consecutive Repetitions. PKDD 2003: 303-314 - [c29]Hunor Albert-Lorincz, Jean-François Boulicaut:
Mining Frequent Sequential Patterns under Regular Expressions: A Highly Adaptive Strategy for Pushing Contraints. SDM 2003: 316-320 - [e1]Jean-François Boulicaut, Saso Dzeroski:
Proceedings of the Second International Workshop on Inductive Databases, 22 September, Cavtat-Dubrovnik, Croatia. Rudjer Boskovic Institute, Zagreb, Croatia 2003, ISBN 953-6690-34-9 [contents] - 2002
- [j2]Baptiste Jeudy, Jean-François Boulicaut:
Optimization of association rule mining queries. Intell. Data Anal. 6(4): 341-357 (2002) - [c28]Marco Botta, Jean-François Boulicaut, Cyrille Masson, Rosa Meo:
A Comparison between Query Languages for the Extraction of Association Rules. DaWaK 2002: 1-10 - [c27]Baptiste Jeudy, Jean-François Boulicaut:
Constraint-Based Discovery and Inductive Queries: Application to Association Rule Mining. Pattern Detection and Discovery 2002: 110-124 - [c26]Matthieu Capelle, Jean-François Boulicaut, Cyrille Masson:
Extraction de motifs séquentiels sous contraintes de similarité. EGC 2002: 65-76 - [c25]Marion Leleu, Jean-François Boulicaut:
Signatures de situations boursières représentées par des séquences d'événements. EGC 2002: 89-100 - [c24]Matthieu Capelle, Cyrille Masson, Jean-François Boulicaut:
Mining Frequent Sequential Patterns under a Similarity Constraint. IDEAL 2002: 1-6 - [c23]Baptiste Jeudy, Jean-François Boulicaut:
Using Condensed Representations for Interactive Association Rule Mining. PKDD 2002: 225-236 - 2001
- [c22]Jean-François Boulicaut, Patrick Marcel, Christophe Rigotti:
Query-Driven Knowledge Discovery via OLAP manipulations. BDA 2001 - [c21]Jean-François Boulicaut, Baptiste Jeudy:
Mining Free Itemsets under Constraints. IDEAS 2001: 322-329 - 2000
- [j1]Jean-François Boulicaut:
A KDD framework to support database audit. Inf. Technol. Manag. 1(3): 195-207 (2000) - [c20]Jean-François Boulicaut, Artur Bykowski, L. Gomez-Chantada:
Association Rule Discovery in Highly-Correlated Data: a Case Study in Web Usage Mining. ADBIS-DASFAA Symposium 2000: 46-55 - [c19]Jean-François Boulicaut, Baptiste Jeudy:
Using Constraints during Frequent Set Mining: a Generic Approach. BDA 2000 - [c18]Jean-François Boulicaut, Artur Bykowski, Baptiste Jeudy:
Towards the Tractable Discovery of Association Rules with Negations. FQAS 2000: 425-434 - [c17]Jean-François Boulicaut, Artur Bykowski:
Frequent Closures as a Concise Representation for Binary Data Mining. PAKDD 2000: 62-73 - [c16]Jean-François Boulicaut, Artur Bykowski, Christophe Rigotti:
Approximation of Frequency Queris by Means of Free-Sets. PKDD 2000: 75-85
1990 – 1999
- 1999
- [c15]Jean-François Boulicaut, Mika Klemettinen, Heikki Mannila:
Modeling KDD Processes within the Inductive Database Framework. DaWaK 1999: 293-302 - [c14]Jean-François Boulicaut, Patrick Marcel, Christophe Rigotti:
Query Driven Knowledge Discovery in Multidimensional Data. DOLAP 1999: 87-93 - [c13]Jean-François Boulicaut:
Query Languages for Knowledge Discovery in Databases. PKDD 1999: 582-583 - 1998
- [c12]Jean-François Boulicaut, Patrick Marcel, François Pinet, Christophe Rigotti:
Spreadsheet Generation from Rule-Based Specifications. DDLP 1998: 59-70 - [c11]Jean-François Boulicaut, Mika Klemettinen, Heikki Mannila:
Querying Inductive Databases: A Case Study on the MINE RULE Operator. PKDD 1998: 194-202 - 1996
- [c10]Jean-Marc Petit, Farouk Toumani, Jean-François Boulicaut, Jacques Kouloumdjian:
Towards the Reverse Engineering of Denormalized Relational Databases. ICDE 1996: 218-227 - [c9]Jean-François Boulicaut, Christophe Rigotti:
Abduction et déduction de structures d'objets: une intégration multiparadigmes. JFPLC 1996: 17-32 - 1994
- [c8]Christophe Rigotti, Mohand-Said Hacid, Jean-François Boulicaut:
Une approche multi-paradigmes our le test d'applications BDOO. BDA 1994 - [c7]Jean-Marc Petit, Jacques Kouloumdjian, Jean-François Boulicaut, Farouk Toumani:
Using Queries to Improve Database Reverse Engineering. ER 1994: 369-386 - [c6]Christophe Rigotti, Mohand-Said Hacid, Jean-François Boulicaut:
F-Logic Programming and Terminological Constraints. ICLP Workshop: Integration of Declarative Paradigms 1994: 1-11 - [c5]Christophe Rigotti, Jean-François Boulicaut, Mohand-Said Hacid:
Vers une typologie des sémantiques opérationnelles pour les extensions de Prolog vers les objets. JFPLC 1994: 223-238 - 1992
- [c4]Sadeph Saidi, Jean-François Boulicaut:
Checking and Debugging of Two-level Grammars. PLILP 1992: 158-171 - 1990
- [c3]Jean Beney, Jean-François Boulicaut:
STARLET: An Affix-Based Compiler Compiler Designed as a Logic Programming System. CC 1990: 71-85 - [c2]Sadeph Saidi, Jean-François Boulicaut:
AFFLOG: une implantation de grammaires à deux niveaux pour l'étude de la Programmation Grammaticale Logique. SPLT 1990: 45-70
1980 – 1989
- 1986
- [c1]Jean Beney, Jean-François Boulicaut:
STARLET: un langage pour une programmation logique fiable. SPLT 1986: 253-
Coauthor Index
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