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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]