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Arnaud Soulet
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- affiliation: Université de Tours, France
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2020 – today
- 2024
- [c67]Youssef Oubelmouh, Frédéric Fargon, Cyril de Runz, Arnaud Soulet, Cyril Veillon:
Identification des motifs séquentiels affectant l'attrition des employés. EGC 2024: 369-376 - 2023
- [j18]Lamine Diop
, Béatrice Markhoff
TTProfiler: Types and Terms Profile Building for Online Cultural Heritage Knowledge Graphs. ACM Journal on Computing and Cultural Heritage 16(3): 61:1-61:22 (2023) - [c66]Youssef Oubelmouh, Frédéric Fargon, Cyril De Runz, Arnaud Soulet, Cyril Veillon:
Identifying Survival-Changing Sequential Patterns for Employee Attrition Analysis. DSAA 2023: 1-10 - [c65]Arnaud Soulet:
Echantillonnage de motifs avec une contrainte de fréquence. EGC 2023: 115-126 - [c64]Hassan Abdallah, Béatrice Markhoff, Arnaud Soulet:
Et si on comprenait la structure de graphes de connaissances comme Wikidata ? IC 2023: 126-131 - [c63]Arnaud Soulet:
Should We Consider On-Demand Analysis in Scale-Free Networks? IDA 2023: 406-418 - [i2]Loïck Lhote, Béatrice Markhoff, Arnaud Soulet:
The Structure and Dynamics of Knowledge Graphs, with Superficiality. CoRR abs/2305.08116 (2023) - 2022
- [j17]Sihem Amer-Yahia, Arnaud Soulet:
Preface. Data Knowl. Eng. 142: 102101 (2022) - [j16]Lamine Diop
Pattern on demand in transactional distributed databases. Inf. Syst. 104: 101908 (2022) - [j15]Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
A Method for Generating Comparison Tables From the Semantic Web. Int. J. Data Warehous. Min. 18(2): 1-20 (2022) - [j14]Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
Découverte de cardinalités maximales significatives dans des bases de connaissances. Rev. Ouverte Intell. Artif. 3(3-4): 223-251 (2022) - [j13]Sihem Amer-Yahia, Angela Bonifati, Cécile Favre, Élisa Fromont, Nicolas Labroche, Guy Melançon
Diversity and Inclusion Activities in EGC - A 2022 Report. SIGKDD Explor. 24(1): 52-56 (2022) - [c62]Lamine Diop, Cheikh Talibouya Diop, Arnaud Giacometti, Arnaud Soulet:
Trie-based Output Space Itemset Sampling. IEEE Big Data 2022: 6-15 - [c61]Arnaud Soulet, François Rioult, Bruno Crémilleux:
A Condensed Survey on Condensed Representations of Patterns. KDID 2022: 1-16 - [e1]Sihem Amer-Yahia, Arnaud Soulet:
Extraction et Gestion des Connaissances, EGC 2022, Blois, France, 24 au 28 janvier 2022. RNTI E-38, Editions RNTI 2022, ISBN 979-10-96289-16-5 [contents] - 2021
- [c60]Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
Comparison Table Generation from Knowledge Bases. ESWC 2021: 179-194 - [c59]Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
VERSUS : générateur de tableaux comparatifs à partir de bases de connaissances. EGC 2021: 23-34 - [c58]Cyril de Runz, Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
Découverte d'indicateurs de classement dans leWeb des données. EGC 2021: 35-46 - [c57]Léo-Paul Renard, Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
Découverte de cardinalités maximales FAIR. EGC 2021: 453-460 - [c56]Arnaud Giacometti
Reservoir Pattern Sampling in Data Streams. ECML/PKDD (1) 2021: 337-352 - [c55]Lamine Diop, Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
TTProfiler: Computing Types and Terms Profiles of Assertional Knowledge Graphs. SWODCH 2021 - 2020
- [j12]Adnan El Moussawi, Arnaud Giacometti, Nicolas Labroche, Arnaud Soulet:
MAPK-means: A clustering algorithm with quantitative preferences on attributes. Intell. Data Anal. 24(2): 459-489 (2020) - [j11]Lamine Diop
Sequential pattern sampling with norm-based utility. Knowl. Inf. Syst. 62(5): 2029-2065 (2020) - [c54]Lamine Diop
Pattern Sampling in Distributed Databases. ADBIS 2020: 60-74
2010 – 2019
- 2019
- [b2]Arnaud Soulet:
Découverte de motifs centrée sur l'utilisateur. (User-Centric Pattern Discovery). François Rabelais University, Tours, France, 2019 - [c53]Lamine Diop, Cheikh Talibouya Diop, Arnaud Giacometti, Dominique Li, Arnaud Soulet:
Découverte de motifs à la demande dans une base de données distribuée. EGC 2019: 21-32 - [c52]Arnaud Soulet, Arnaud Giacometti, Béatrice Markhoff, Fabian M. Suchanek:
Représentativité des bases de connaissances avec la loi de Benford généralisée. IC 2019: 80 - [c51]Arnaud Giacometti
Mining Significant Maximum Cardinalities in Knowledge Bases. ISWC (1) 2019: 182-199 - [c50]Arnaud Soulet
Anytime Large-Scale Analytics of Linked Open Data. ISWC (1) 2019: 576-592 - 2018
- [j10]Khanh-Chuong Duong, Mostafa Bamha, Arnaud Giacometti, Dominique Li, Arnaud Soulet, Christel Vrain:
MapFIM+: Memory Aware Parallelized Frequent Itemset Mining In Very Large Datasets. Trans. Large Scale Data Knowl. Centered Syst. 39: 200-225 (2018) - [c49]Lamine Diop, Cheikh Talibouya Diop, Arnaud Giacometti, Dominique Li, Arnaud Soulet:
Echantillonnage de motifs séquentiels sous contrainte sur la norme. EGC 2018: 35-46 - [c48]Lamine Diop
Sequential Pattern Sampling with Norm Constraints. ICDM 2018: 89-98 - [c47]Bruno Crémilleux, Arnaud Giacometti, Arnaud Soulet:
How Your Supporters and Opponents Define Your Interestingness. ECML/PKDD (1) 2018: 373-389 - [c46]El Arby Sidi Aly, Mohamed Lamine Diakité, Arnaud Giacometti, Béatrice Markhoff, Arnaud Soulet:
Découverte de cardinalité maximale contextuelle dans les bases de connaissances(Mining contextual maximum cardinality in knowledge bases). CNIA+RJCIA 2018: 86-93 - [c45]Arnaud Giacometti, Arnaud Soulet:
Dense Neighborhood Pattern Sampling in Numerical Data. SDM 2018: 756-764 - [c44]Arnaud Soulet, Arnaud Giacometti, Béatrice Markhoff, Fabian M. Suchanek:
Representativeness of Knowledge Bases with the Generalized Benford's Law. ISWC (1) 2018: 374-390 - 2017
- [j9]Willy Ugarte
Skypattern mining: From pattern condensed representations to dynamic constraint satisfaction problems. Artif. Intell. 244: 48-69 (2017) - [c43]Khanh-Chuong Duong, Mostafa Bamha, Arnaud Giacometti, Dominique Li, Arnaud Soulet, Christel Vrain:
MapFIM: Memory Aware Parallelized Frequent Itemset Mining in Very Large Datasets. DEXA (1) 2017: 478-495 - [c42]Moditha Hewasinghage, Suela Isaj, Arnaud Giacometti, Arnaud Soulet:
Description interactive de l'intérêt de l'utilisateur via l'échantillonnage de motifs. EGC 2017: 285-296 - [c41]Adnan El Moussawi, Philippe De Guis, Arnaud Giacometti, Nicolas Labroche, Arnaud Soulet:
Prototype de clustering exploratoire pour l'aide à la segmentation des clients. EGC 2017: 457-460 - [c40]Arnaud Giacometti, Arnaud Soulet:
Interactive Pattern Sampling for Characterizing Unlabeled Data. IDA 2017: 99-111 - 2016
- [j8]Arnaud Giacometti, Arnaud Soulet
Anytime algorithm for frequent pattern outlier detection. Int. J. Data Sci. Anal. 2(3-4): 119-130 (2016) - [c39]Arnaud Soulet:
Two Decades of Pattern Mining: Principles and Methods. eBISS 2016: 59-78 - [c38]Arnaud Giacometti, Arnaud Soulet:
Détection de données aberrantes à partir de motifs fréquents sans énumération exhaustive. EGC 2016: 51-62 - [c37]Adnan El Moussawi, Ahmed Cheriat, Arnaud Giacometti, Nicolas Labroche, Arnaud Soulet:
Clustering par apprentissage de distance guidé par des préférences sur les attributs. EGC 2016: 333-344 - [c36]Adnan El Moussawi, Ahmed Cheriat, Arnaud Giacometti, Nicolas Labroche, Arnaud Soulet:
Clustering with Quantitative User Preferences on Attributes. ICTAI 2016: 383-387 - [c35]Arnaud Giacometti, Arnaud Soulet:
Frequent Pattern Outlier Detection Without Exhaustive Mining. PAKDD (2) 2016: 196-207 - 2015
- [j7]Sandra de Amo
Contextual preference mining for user profile construction. Inf. Syst. 49: 182-199 (2015) - [c34]Arnaud Soulet, François Rioult:
Exact and Approximate Minimal Pattern Mining. EGC (best of volume) 2015: 61-81 - [c33]Bruno Crémilleux, Arnaud Giacometti, Arnaud Soulet:
Qualité et complexité en évaluation des mesures d'intérêt. EGC 2015: 335-346 - 2014
- [c32]Arnaud Soulet, François Rioult:
Extraire les motifs minimaux efficacement et en profondeur. EGC 2014: 383-394 - [c31]Arnaud Giacometti, Dominique Li, Arnaud Soulet:
Construction de profils de préférences contextuelles basée sur l'extraction de motifs séquentiels. EGC 2014: 419-430 - [c30]Jacques Bouaud, Arnaud Soulet, Jean-Philippe Spano, Jean-Pierre Lefranc, Isabelle Cojean-Zelek, Brigitte Blaszka-Jaulerry, Laurent Zelek, Axel Durieux, Christophe Tournigand, Nizar Messai, Alexandra Rousseau, Brigitte Séroussi:
Quels sont les patients atteints d'un cancer du sein dont la décision de prise en charge thérapeutique bénéficie de l'utilisation d'un système d'aide à la décision ? Un exemple utilisant la fouille de données et OncoDoc2. IC 2014: 107-118 - [c29]Arnaud Soulet, François Rioult:
Efficiently Depth-First Minimal Pattern Mining. PAKDD (1) 2014: 28-39 - [c28]Arnaud Giacometti, Dominique H. Li, Arnaud Soulet:
Balancing the Analysis of Frequent Patterns. PAKDD (1) 2014: 53-64 - 2013
- [j6]Arnaud Giacometti, Dominique H. Li, Patrick Marcel
20 years of pattern mining: a bibliometric survey. SIGKDD Explor. 15(1): 41-50 (2013) - [j5]Damien Nouvel, Jean-Yves Antoine, Nathalie Friburger, Arnaud Soulet:
Fouille de règles d'annotation pour la reconnaissance d'entités nommées. Trait. Autom. des Langues 54(2): 13-41 (2013) - [c27]Arnaud Giacometti, Dominique Haoyuan Li, Arnaud Soulet:
20 ans de découverte de motifs : une étude bibliographique quantitative. EGC 2013: 133-144 - [c26]Brigitte Séroussi
Which Patients may benefit from the Use of a Decision Support System to Improve Compliance of Physician Decisions with Clinical Practice Guidelines: A Case Study with Breast Cancer involving Data Mining. MedInfo 2013: 534-538 - [c25]Damien Nouvel, Jean-Yves Antoine, Nathalie Friburger, Arnaud Soulet:
Mining Partial Annotation Rules for Named Entity Recognition (Fouille de règles d'annotation partielles pour la reconnaissance des entités nommées) [in French]. TALN (1) 2013: 421-434 - 2012
- [c24]Brigitte Séroussi, Arnaud Soulet, Nizar Messai, Cédric Laouenan, France Mentré, Jacques Bouaud:
Patient clinical profiles associated with physician non-compliance despite the use of a guideline-based decision support system: a case study with OncoDoc2 using data mining techniques. AMIA 2012 - [c23]Sandra de Amo, Mouhamadou Saliou Diallo, Cheikh Talibouya Diop, Arnaud Giacometti, Haoyuan D. Li, Arnaud Soulet:
Mining Contextual Preference Rules for Building User Profiles. DaWaK 2012: 229-242 - 2011
- [j4]Arnaud Giacometti, Patrick Marcel
Query Recommendations for OLAP Discovery-Driven Analysis. Int. J. Data Warehous. Min. 7(2): 1-25 (2011) - [c22]Arnaud Giacometti, Patrick Marcel
A Relational View of Pattern Discovery. DASFAA (1) 2011: 153-167 - [c21]Arnaud Giacometti, Patrick Marcel, Arnaud Soulet:
Equilibrer l'analyse des motifs fréquents. EGC 2011: 47-52 - [c20]Damien Nouvel, Arnaud Soulet:
Annotation d'entités nommées par extraction de règles de transduction. EGC 2011: 119-130 - [c19]Arnaud Soulet, Chedy Raïssi, Marc Plantevit
Mining Dominant Patterns in the Sky. ICDM 2011: 655-664 - [c18]Arnaud Soulet, Bruno Crémilleux, Marc Plantevit
Summarizing Contrasts by Recursive Pattern Mining. ICDM Workshops 2011: 1155-1162 - 2010
- [c17]Marie Ndiaye, Cheikh Talibouya Diop, Arnaud Giacometti, Patrick Marcel
Cube Based Summaries of Large Association Rule Sets. ADMA (1) 2010: 73-85 - [c16]Damien Nouvel, Arnaud Soulet, Jean-Yves Antoine, Nathalie Friburger, Denis Maurel:
Reconnaissance d'entités nommées : enrichissement d'un système à base de connaissances à partir de techniques de fouille de textes. TALN (Articles courts) 2010: 201-206
2000 – 2009
- 2009
- [j3]Arnaud Soulet, Bruno Crémilleux:
Mining constraint-based patterns using automatic relaxation. Intell. Data Anal. 13(1): 109-133 (2009) - [c15]Arnaud Giacometti, Patrick Marcel
Query recommendations for OLAP discovery driven analysis. DOLAP 2009: 81-88 - [c14]Arnaud Giacometti, Eynollah Khanjari Miyaneh, Patrick Marcel
A Framework for Pattern-Based Global Models. IDEAL 2009: 433-440 - 2008
- [j2]Arnaud Soulet, Bruno Crémilleux:
Adequate condensed representations of patterns. Data Min. Knowl. Discov. 17(1): 94-110 (2008) - [j1]Jirí Kléma, Sylvain Blachon, Arnaud Soulet, Bruno Crémilleux, Olivier Gandrillon:
Constraint-Based Knowledge Discovery from SAGE Data. Silico Biol. 8(2): 157-175 (2008) - [c13]Bruno Crémilleux, Arnaud Soulet:
Discovering Knowledge from Local Patterns with Global Constraints. ICCSA (2) 2008: 1242-1257 - [c12]Arnaud Soulet, Bruno Crémilleux:
Adequate Condensed Representations of Patterns. ECML/PKDD (1) 2008: 20-21 - 2007
- [c11]Arnaud Soulet, Bruno Crémilleux:
Extraction des Top-k Motifs par Approximer-et-Pousser. EGC 2007: 271-282 - [i1]Bruno Crémilleux, Arnaud Soulet:
Discovering Knowledge from Local Patterns with Global Constraints. Parallel Universes and Local Patterns 2007 - 2006
- [b1]Arnaud Soulet:
Un cadre générique de découverte de motifs sous contraintes fondées sur des primitives. (A generic framework for discovering patterns under primitive-based constraints). University of Caen Normandy, France, 2006 - [c10]Jirí Kléma
Mining Plausible Patterns from Genomic Data. CBMS 2006: 183-190 - [c9]Arnaud Soulet, Jirí Kléma, Bruno Crémilleux:
Efficient Mining Under Rich Constraints Derived from Various Datasets. KDID 2006: 223-239 - 2005
- [c8]Loïck Lhote, François Rioult, Arnaud Soulet:
Average Number of Frequent and Closed Patterns in Random Databases. CAP 2005: 345-360 - [c7]Loïck Lhote, François Rioult, Arnaud Soulet:
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases. ICDM 2005: 713-716 - [c6]Arnaud Soulet, Bruno Crémilleux:
Optimizing Constraint-Based Mining by Automatically Relaxing Constraints. ICDM 2005: 777-780 - [c5]Arnaud Soulet, Bruno Crémilleux:
Exploiting Virtual Patterns for Automatically Pruning the Search Space. KDID 2005: 202-221 - [c4]Arnaud Soulet, Bruno Crémilleux:
An Efficient Framework for Mining Flexible Constraints. PAKDD 2005: 661-671 - 2004
- [c3]Arnaud Soulet, Bruno Crémilleux, François Rioult:
Représentation condensée de motifs émergents. EGC 2004: 265-276 - [c2]Arnaud Soulet, Bruno Crémilleux, François Rioult:
Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures. KDID 2004: 173-190 - [c1]Arnaud Soulet, Bruno Crémilleux, François Rioult:
Condensed Representation of Emerging Patterns. PAKDD 2004: 127-132
Coauthor Index
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last updated on 2024-11-08 21:32 CET by the dblp team
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