| Anytime Mining Of Sequential Discriminative Patterns In Labeled Sequences | 0 | 0.34 | 2021 |
| Mining evolutions of complex spatial objects using a single-attributed Directed Acyclic Graph | 0 | 0.34 | 2020 |
| Découverte de sous-groupes à partir de données séquentielles par échantillonnage et optimisation locale. | 0 | 0.34 | 2019 |
| SeqScout: Using a Bandit Model to Discover Interesting Subgroups in Labeled Sequences | 2 | 0.37 | 2019 |
| Anytime discovery of a diverse set of patterns with Monte Carlo tree search. | 0 | 0.34 | 2018 |
| A Proposition for Sequence Mining Using Pattern Structures. | 1 | 0.37 | 2017 |
| What Did I Do Wrong in My MOBA Game? Mining Patterns Discriminating Deviant Behaviours | 2 | 0.36 | 2016 |
| Any-time Diverse Subgroup Discovery with Monte Carlo Tree Search. | 0 | 0.34 | 2016 |
| h(odor): Interactive Discovery of Hypotheses on the Structure-Odor Relationship in Neuroscience. | 0 | 0.34 | 2016 |
| Local Pattern Detection in Attributed Graphs. | 3 | 0.39 | 2016 |
| Interpreting communities based on the evolution of a dynamic attributed network | 5 | 0.41 | 2015 |
| Vers la découverte de modèles exceptionnels locaux : des règles descriptives liant les molécules à leurs odeurs. | 0 | 0.34 | 2015 |
| Extraction complète efficace de chemins pondérés dans un a-DAG. | 0 | 0.34 | 2015 |
| Une méthode pour caractériser les communautés des réseaux dynamiques à attributs. | 0 | 0.34 | 2014 |
| Mining Balanced Sequential Patterns in RTS Games. | 0 | 0.34 | 2014 |
| Improving pattern discovery relevancy by deriving constraints from expert models. | 0 | 0.34 | 2014 |
| Granularité des motifs de co-variations dans des graphes attribués dynamiques. | 0 | 0.34 | 2014 |
| A method for characterizing communities in dynamic attributed complex networks. | 4 | 0.41 | 2014 |
| Granularity of Co-evolution Patterns in Dynamic Attributed Graphs. | 3 | 0.38 | 2014 |
| Fouille de motifs séquentiels pour l'élicitation de stratégies à partir de traces d'interactions entre agents en compétition. | 0 | 0.34 | 2014 |
| Closed and noise-tolerant patterns in n-ary relations | 22 | 0.71 | 2013 |
| Parameter-free classification in multi-class imbalanced data sets. | 3 | 0.37 | 2013 |
| Trend Mining in Dynamic Attributed Graphs | 8 | 0.52 | 2013 |
| Weighted path as a condensed pattern in a single attributed DAG | 1 | 0.36 | 2013 |
| Extraction de motifs condensés dans un unique graphe orienté acyclique attribué. | 0 | 0.34 | 2013 |
| Mining Disjunctive Rules in Dynamic Graphs. | 1 | 0.35 | 2012 |
| Cohesive Co-evolution Patterns in Dynamic Attributed Graphs. | 18 | 0.66 | 2012 |
| Extraction d'arbres spatio-temporels d'itemsets pour le suivi environnemental. | 0 | 0.34 | 2012 |
| Extraction de co-variations entre des propriétés de sommets et leur position topologique dans un graphe attribué. | 0 | 0.34 | 2012 |
| Application-independent feature construction based on almost-closedness properties | 3 | 0.38 | 2012 |
| Extraction sous contraintes d'ensembles de cliques homogènes | 0 | 0.34 | 2011 |
| Multidimensional Association Rules in Boolean Tensors. | 7 | 0.52 | 2011 |
| Comparing Intended and Real Usage in Web Portal: Temporal Logic and Data Mining | 1 | 0.35 | 2010 |
| Discovering Inter-Dimensional Rules in Dynamic Graphs. | 0 | 0.34 | 2010 |
| Extracting signature motifs from promoter sets of differentially expressed genes | 2 | 0.38 | 2009 |
| Application-Independent Feature Construction from Noisy Samples | 1 | 0.34 | 2009 |
| Agglomerating local patterns hierarchically with ALPHA | 1 | 0.35 | 2009 |
| Closed patterns meet n-ary relations | 64 | 2.06 | 2009 |
| Advances in Intelligent Data Analysis VIII, 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009. Proceedings | 33 | 2.95 | 2009 |
| Construction de descripteurs pour classer à partir d'exemples bruités | 0 | 0.34 | 2009 |
| Discovering Relevant Cross-Graph Cliques in Dynamic Networks | 7 | 0.46 | 2009 |
| Extraction de motifs fermés dans des relations n-aires bruitées | 0 | 0.34 | 2009 |
| Co-classification sous contraintes par la somme des résidus quadratiques | 0 | 0.34 | 2008 |
| Constrained Co-clustering of Gene Expression Data | 21 | 0.80 | 2008 |
| Data Peeler: Contraint-Based Closed Pattern Mining in n-ary Relations | 18 | 0.79 | 2008 |
| Discovery Science, 11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008. Proceedings | 28 | 1.81 | 2008 |
| Feature construction based on closedness properties is not that simple | 6 | 0.40 | 2008 |
| If Constraint-Based Mining is the Answer: What is the Constraint? (Invited Talk) | 0 | 0.34 | 2008 |
| Numerical Data Co-clustering via Sum-Squared Residue Minimization and User-defined Constraint Satisfaction | 0 | 0.34 | 2008 |
| A Parameter-Free Associative Classification Method | 2 | 0.37 | 2008 |
