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Marc Plantevit
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- affiliation: Université Lyon 1, LIRIS, France
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2020 – today
- 2024
- [j26]Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet
:
On GNN explainability with activation rules. Data Min. Knowl. Discov. 38(5): 3227-3261 (2024) - [c67]Alessio Ragno, Marc Plantevit, Céline Robardet, Roberto Capobianco:
Transparent Explainable Logic Layers. ECAI 2024: 914-921 - [c66]Arthur Batel, Idir Benouaret, Joan Fruitet, Marc Plantevit, Céline Robardet:
A Simple Yet Effective Interpretable Bayesian Personalized Ranking for Cognitive Diagnosis. ECAI 2024: 2386-2393 - [c65]Thibaut Chataing, Julien Perez, Marc Plantevit, Céline Robardet:
DiffVersify: a Scalable Approach to Differentiable Pattern Mining with Coverage Regularization. ECML/PKDD (6) 2024: 407-422 - [i8]Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet:
On GNN explanability with activation rules. CoRR abs/2406.11594 (2024) - 2023
- [j25]Mouloud Iferroudjene, Corentin Lonjarret, Céline Robardet
Methods for explaining Top-N recommendations through subgroup discovery. Data Min. Knowl. Discov. 37(2): 833-872 (2023) - [j24]Maëlle Moranges
Using Subgroup Discovery to Relate Odor Pleasantness and Intensity to Peripheral Nervous System Reactions. IEEE Trans. Affect. Comput. 14(3): 2005-2019 (2023) - [c64]Léonard Tschora, Tias Guns, Erwan Pierre, Marc Plantevit, Céline Robardet:
Electricity Price Forecasting based on Order Books: a differentiable optimization approach. DSAA 2023: 1-10 - [c63]Youcef Remil, Anes Bendimerad, Mathieu Chambard, Romain Mathonat, Marc Plantevit, Mehdi Kaytoue:
Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical Targets. ICDM (Workshops) 2023: 1221-1230 - [c62]Léonard Tschora, Erwan Pierre, Marc Plantevit, Céline Robardet:
Forecasting Electricity Prices: An Optimize Then Predict-Based Approach. IDA 2023: 446-458 - [i7]Youcef Remil, Anes Bendimerad, Mathieu Chambard, Romain Mathonat, Marc Plantevit, Mehdi Kaytoue:
Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical Targets. CoRR abs/2310.00781 (2023) - 2022
- [j23]Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet:
In pursuit of the hidden features of GNN's internal representations. Data Knowl. Eng. 142: 102097 (2022) - [c61]Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet:
Qu'est-ce que mon GNN capture vraiment ? Exploration des représentations internes d'un GNN. EGC 2022: 159-170 - [c60]Youcef Remil, Anes Bendimerad, Marc Plantevit, Céline Robardet, Mehdi Kaytoue:
Découverte de sous-groupes de prédictions interprétables pour le triage d'incidents. EGC 2022: 411-418 - [c59]Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet:
What Does My GNN Really Capture? On Exploring Internal GNN Representations. IJCAI 2022: 747-752 - [c58]Pierre Duluard, Xinqing Li, Marc Plantevit, Céline Robardet, Romain Vuillemot:
Discovering and Visualizing Tactics in a Table Tennis Game Based on Subgroup Discovery. MLSA@PKDD/ECML 2022: 101-112 - [c57]Ataollah Kamal, Elouan Vincent, Marc Plantevit, Céline Robardet:
Improving the Quality of Rule-Based GNN Explanations. PKDD/ECML Workshops (1) 2022: 467-482 - 2021
- [j22]Corentin Lonjarret, Roch Auburtin, Céline Robardet
Sequential recommendation with metric models based on frequent sequences. Data Min. Knowl. Discov. 35(3): 1087-1133 (2021) - [j21]Anes Bendimerad
User-Driven Geolocated Event Detection in Social Media. IEEE Trans. Knowl. Data Eng. 33(2): 796-809 (2021) - [c56]Youcef Remil, Anes Bendimerad
Interpretable Summaries of Black Box Incident Triaging with Subgroup Discovery. DSAA 2021: 1-10 - [i6]Youcef Remil, Anes Bendimerad
Interpretable Summaries of Black Box Incident Triaging with Subgroup Discovery. CoRR abs/2108.03013 (2021) - 2020
- [j20]Anes Bendimerad
SIAS-miner: mining subjectively interesting attributed subgraphs. Data Min. Knowl. Discov. 34(2): 355-393 (2020) - [j19]Adnene Belfodil
Identifying exceptional (dis)agreement between groups. Data Min. Knowl. Discov. 34(2): 394-442 (2020) - [c55]Corentin Lonjarret, Céline Robardet, Marc Plantevit
Why Should I Trust This Item? Explaining the Recommendations of any Model. DSAA 2020: 526-535 - [c54]Anes Bendimerad
Gibbs Sampling Subjectively Interesting Tiles. IDA 2020: 80-92 - [i5]Corentin Lonjarret, Roch Auburtin, Céline Robardet, Marc Plantevit
Sequential recommendation with metric models based on frequent sequences. CoRR abs/2008.05587 (2020)
2010 – 2019
- 2019
- [j18]Mohamed-Ali Hammal, Hélène Mathian, Luc Merchez, Marc Plantevit
Rank correlated subgroup discovery. J. Intell. Inf. Syst. 53(2): 305-328 (2019) - [j17]Carmen C. Licon
Chemical features mining provides new descriptive structure-odor relationships. PLoS Comput. Biol. 15(4) (2019) - [c53]Mohamed-Ali Hammal, Bernardo A. Abreu, Marc Plantevit, Céline Robardet:
Sampling Rank Correlated Subgroups. DCAI 2019: 217-225 - [c52]Adnene Belfodil, Aimene Belfodil, Anes Bendimerad
FSSD - A Fast and Efficient Algorithm for Subgroup Set Discovery. DSAA 2019: 91-99 - [c51]Mohamed-Ali Hammal, Céline Robardet, Marc Plantevit:
Quand les sous-groupes rencontrent les graduels : découverte de sous-groupes identifiant des corrélations exceptionnelles. EGC 2019: 201-212 - [c50]Corentin Lonjarret, Marc Plantevit, Céline Robardet, Roch Auburtin:
Recommandation séquentielle à base de séquences fréquentes. EGC 2019: 267-272 - [c49]Charles de Lacombe, Antoine Morel, Adnene Belfodil, François Portet, Cyril Labbé, Sylvie Cazalens, Marc Plantevit, Philippe Lamarre:
Analyse de comportements relatifs exceptionnels expliquée par des textes : les votes du parlement européen. EGC 2019: 437-440 - [c48]Anes Bendimerad
Contrastive Antichains in Hierarchies. KDD 2019: 294-304 - [c47]Adnene Belfodil, Wouter Duivesteijn, Marc Plantevit
DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups. ECML/PKDD (1) 2019: 3-20 - [i4]Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie:
Mining Subjectively Interesting Attributed Subgraphs. CoRR abs/1905.03040 (2019) - 2018
- [b2]Marc Plantevit:
Contributions to Pattern Mining in Augmented Graphs. (Contributions à la découverte de motifs dans des graphes augmentés). Claude Bernard University Lyon 1, France, 2018 - [j16]Ahmed Anes Bendimerad
Mining exceptional closed patterns in attributed graphs. Knowl. Inf. Syst. 56(1): 1-25 (2018) - [c46]Maëlle Moranges
Exceptional Attributed Subgraph Mining to Understand the Olfactory Percept. DS 2018: 276-291 - 2017
- [j15]Willy Ugarte
Skypattern mining: From pattern condensed representations to dynamic constraint satisfaction problems. Artif. Intell. 244: 48-69 (2017) - [j14]Mehdi Kaytoue
Exceptional contextual subgraph mining. Mach. Learn. 106(8): 1171-1211 (2017) - [c45]Ahmed Anes Bendimerad
Contextual Subgraph Discovery with Mobility Models. COMPLEX NETWORKS 2017: 477-489 - [c44]Adnene Belfodil
Flash Points: Discovering Exceptional Pairwise Behaviors in Vote or Rating Data. ECML/PKDD (2) 2017: 442-458 - 2016
- [j13]Marc Plantevit, Céline Robardet, Vasile-Marian Scuturici:
Graph dependency construction based on interval-event dependencies detection in data streams. Intell. Data Anal. 20(2): 223-256 (2016) - [c43]Jean-François Boulicaut, Marc Plantevit
Local Pattern Detection in Attributed Graphs. Solving Large Scale Learning Tasks 2016: 168-183 - [c42]Guillaume Bosc, Jérôme Golebiowski, Moustafa Bensafi, Céline Robardet, Marc Plantevit
Local Subgroup Discovery for Eliciting and Understanding New Structure-Odor Relationships. DS 2016: 19-34 - [c41]Aimene Belfodil, Mehdi Kaytoue, Céline Robardet, Marc Plantevit, Julien Zarka:
Une méthode de découverte de motifs contextualisés dans les traces de mobilité d'une personne. EGC 2016: 63-68 - [c40]Ahmed Anes Bendimerad
Unsupervised Exceptional Attributed Sub-Graph Mining in Urban Data. ICDM 2016: 21-30 - [c39]Guillaume Bosc, Marc Plantevit
h(odor): Interactive Discovery of Hypotheses on the Structure-Odor Relationship in Neuroscience. ECML/PKDD (3) 2016: 17-21 - 2015
- [j12]Peggy Cellier
Sequential pattern mining for discovering gene interactions and their contextual information from biomedical texts. J. Biomed. Semant. 6: 27 (2015) - [j11]Günce Keziban Orman
Interpreting communities based on the evolution of a dynamic attributed network. Soc. Netw. Anal. Min. 5(1): 20:1-20:22 (2015) - [j10]Mehdi Kaytoue, Yoann Pitarch, Marc Plantevit
What effects topological changes in dynamic graphs? - Elucidating relationships between vertex attributes and the graph structure. Soc. Netw. Anal. Min. 5(1): 55:1-55:17 (2015) - [c38]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 - [c37]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 - [c36]Pierre Houdyer, Albrecht Zimmermann, Mehdi Kaytoue, Marc Plantevit
Gazouille: Detecting and Illustrating Local Events from Geolocalized Social Media Streams. ECML/PKDD (3) 2015: 276-280 - [i3]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) - 2014
- [j9]Pierre-Nicolas Mougel, Christophe Rigotti, Marc Plantevit
Finding maximal homogeneous clique sets. Knowl. Inf. Syst. 39(3): 579-608 (2014) - [c35]Mehdi Kaytoue, Yoann Pitarch, Marc Plantevit
Triggering patterns of topology changes in dynamic graphs. ASONAM 2014: 158-165 - [c34]Günce Keziban Orman
A method for characterizing communities in dynamic attributed complex networks. ASONAM 2014: 481-484 - [c33]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 - [c32]Elise Desmier, Marc Plantevit, Jean-François Boulicaut:
Granularité des motifs de co-variations dans des graphes attribués dynamiques. EGC 2014: 431-442 - [c31]Pierre Holat, Marc Plantevit
Sequence Classification Based on Delta-Free Sequential Patterns. ICDM 2014: 170-179 - [c30]Elise Desmier, Marc Plantevit, Céline Robardet, Jean-François Boulicaut:
Granularity of Co-evolution Patterns in Dynamic Attributed Graphs. IDA 2014: 84-95 - [c29]Marc Plantevit
Temporal Dependency Detection Between Interval-Based Event Sequences. NFMCP 2014: 132-146 - [i2]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
- [j8]Kim-Ngan Nguyen, Loïc Cerf, Marc Plantevit
Discovering descriptive rules in relational dynamic graphs. Intell. Data Anal. 17(1): 49-69 (2013) - [j7]Adriana Prado, Marc Plantevit
Mining Graph Topological Patterns: Finding Covariations among Vertex Descriptors. IEEE Trans. Knowl. Data Eng. 25(9): 2090-2104 (2013) - [c28]Céline Robardet, Vasile-Marian Scuturici, Marc Plantevit, Antoine Fraboulet:
When TEDDY meets GrizzLY: temporal dependency discovery for triggering road deicing operations. KDD 2013: 1490-1493 - [c27]Elise Desmier, Marc Plantevit
Trend Mining in Dynamic Attributed Graphs. ECML/PKDD (1) 2013: 654-669 - [i1]Günce Keziban Orman, Vincent Labatut, Marc Plantevit
Une méthode pour caractériser les communautés des réseaux dynamiques à attributs. CoRR abs/1312.4676 (2013) - 2012
- [c26]Elise Desmier, Marc Plantevit
Cohesive Co-evolution Patterns in Dynamic Attributed Graphs. Discovery Science 2012: 110-124 - [c25]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 - [c24]Julien Salotti, Marc Plantevit
Supporting the Discovery of Relevant Topological Patterns in Attributed Graphs. ICDM Workshops 2012: 898-901 - [c23]Kim-Ngan Nguyen, Marc Plantevit
Mining Disjunctive Rules in Dynamic Graphs. RIVF 2012: 1-6 - 2011
- [c22]Marc Plantevit, Chedy Raïssi, Bruno Crémilleux:
Motifs séquentiels delta-libres. EGC 2011: 35-46 - [c21]Pierre-Nicolas Mougel, Marc Plantevit, Christophe Rigotti, Olivier Gandrillon, Jean-François Boulicaut:
Extraction sous contraintes d'ensembles de cliques homogènes. EGC 2011: 443-454 - [c20]Arnaud Soulet, Chedy Raïssi, Marc Plantevit
Mining Dominant Patterns in the Sky. ICDM 2011: 655-664 - [c19]Arnaud Soulet, Bruno Crémilleux, Marc Plantevit
Summarizing Contrasts by Recursive Pattern Mining. ICDM Workshops 2011: 1155-1162 - [c18]Kim-Ngan Nguyen, Loïc Cerf, Marc Plantevit, Jean-François Boulicaut:
Multidimensional Association Rules in Boolean Tensors. SDM 2011: 570-581 - 2010
- [j6]Yoann Pitarch, Anne Laurent, Marc Plantevit, Pascal Poncelet
Fenêtres sur cube. Ingénierie des Systèmes d Inf. 15(1): 9-33 (2010) - [j5]Marc Plantevit
Mining multidimensional and multilevel sequential patterns. ACM Trans. Knowl. Discov. Data 4(1): 4:1-4:37 (2010) - [c17]Peggy Cellier, Thierry Charnois, Marc Plantevit
Sequential Patterns to Discover and Characterise Biological Relations. CICLing 2010: 537-548 - [c16]Peggy Cellier, Thierry Charnois, Marc Plantevit
Recursive Sequence Mining to Discover Named Entity Relations. IDA 2010: 30-41 - [c15]Kim-Ngan Nguyen, Loïc Cerf, Marc Plantevit, Jean-François Boulicaut:
Discovering Inter-Dimensional Rules in Dynamic Graphs. NyNaK 2010
2000 – 2009
- 2009
- [j4]Marc Plantevit
Mining convergent and divergent sequences in multidimensional data. Int. J. Bus. Intell. Data Min. 4(3/4): 242-266 (2009) - [j3]Marc Plantevit
Combining sequence and itemset mining to discover named entities in biomedical texts: a new type of pattern. Int. J. Data Min. Model. Manag. 1(2): 119-148 (2009) - [j2]Thierry Charnois, Marc Plantevit, Christophe Rigotti, Bruno Crémilleux:
Sequential Data Mining for Information Extraction from Texts. Trait. Autom. des Langues 50(3): 59-87 (2009) - [c14]Yoann Pitarch, Anne Laurent, Marc Plantevit
Multidimensional Data Stream Summarization Using Extended Tilted-Time Windows. AINA Workshops 2009: 250-254 - [c13]Marc Plantevit
Condensed Representation of Sequential Patterns According to Frequency-Based Measures. IDA 2009: 155-166 - [c12]Marc Plantevit, Thierry Charnois:
Motifs séquentiels pour l'extraction d'information : illustration sur le problème de la détection d'interactions entre gènes. TALN (Articles longs) 2009: 141-150 - [p1]Marc Plantevit, Anne Laurent, Maguelonne Teisseire:
OLAP-Sequential Mining: Summarizing Trends from Historical. New Trends in Data Warehousing and Data Analysis 2009: 1-23 - 2008
- [b1]Marc Plantevit:
Extraction De Motifs Séquentiels Dans Des Données Multidimensionelles. (Mining Sequential Patterns In Multidimensional Data). Montpellier 2 University, France, 2008 - [j1]Marc Plantevit, Anne Laurent, Maguelonne Teisseire:
Motifs séquentiels multidimensionnels et mesure. Différentes techniques pour calculer le support. Ingénierie des Systèmes d Inf. 13(6): 9-32 (2008) - [c11]Marc Plantevit
Up and Down: Mining Multidimensional Sequential Patterns Using Hierarchies. DaWaK 2008: 156-165 - [c10]Chedy Raïssi, Marc Plantevit
Mining Multidimensional Sequential Patterns over Data Streams. DaWaK 2008: 263-272 - [c9]Marc Plantevit, Anne Laurent, Maguelonne Teisseire:
Fouille de Données Multidimensionnelles : Différentes Stratégies pour Prendre en Compte la Mesure. EDA 2008: 61-75 - [c8]Marc Plantevit, Anne Laurent, Maguelonne Teisseire:
Extraction de Motifs Séquentiels Multidimensionnels Clos sans Gestion d'Ensemble de Candidats. EGC 2008: 541-546 - 2007
- [c7]Marc Plantevit
Mining unexpected multidimensional rules. DOLAP 2007: 89-96 - [c6]Marc Plantevit, Anne Laurent, Maguelonne Teisseire:
Extraction d'outliers dans des cubes de données : une aide à la navigation. EDA 2007: 113-130 - [c5]Marc Plantevit, Anne Laurent, Maguelonne Teisseire:
Extraction de séquences multidimensionnelles convergentes et divergentes. EGC 2007: 283-294 - 2006
- [c4]Marc Plantevit
HYPE: mining hierarchical sequential patterns. DOLAP 2006: 19-26 - [c3]Marc Plantevit, Anne Laurent, Maguelonne Teisseire:
Hype : Prise en compte des hiérarchies lors de l'extraction de motifs séquentiels multidimensionnels. EDA 2006: 155-174 - 2005
- [c2]Marc Plantevit, Yeow Wei Choong, Anne Laurent, Dominique Laurent, Maguelonne Teisseire:
Motifs séquentiels multidimensionnels étoilés. BDA 2005 - [c1]Marc Plantevit
M2SP: Mining Sequential Patterns Among Several Dimensions. PKDD 2005: 205-216
Coauthor Index
Ahmed Anes Bendimerad
aka: Anes Bendimerad
aka: Anes Bendimerad
Mehdi Kaytoue-Uberall
aka: Mehdi Kaytoue
aka: Mehdi Kaytoue
[j26] [c67] [c66] [c65] [i8] [j25] [c64] [c62] [j23] [c61] [c60] [c59] [c58] [c57] [j22] [j21] [c56] [i6] [j20] [c55] [c54] [i5] [j18] [j17] [c53] [c52] [c51] [c50] [c48] [i4] [j16] [c46] [j14] [c45] [j13] [c43] [c42] [c41] [c40] [j10] [c37] [c36] [c35] [c30] [c29] [j7] [c28] [c27] [c26] [c25] [c24]
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