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lirmm-00753791v1  Conference papers
Chongsheng ZhangFlorent MassegliaXiangliang Zhang. Modeling and Clustering Users with Evolving Profiles in Usage Streams
TIME'2012: 19th International Symposium on Temporal Representation and Reasoning, Sep 2012, United Kingdom. pp.133-140
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lirmm-00753807v1  Conference papers
Chongsheng ZhangFlorent MassegliaXiangliang Zhang. Discovering Highly Informative Feature Set Over High Dimensions
ICTAI: International Conference on Tools with Artificial Intelligence, Nov 2012, Athens, Greece. pp.1059-1064, ⟨10.1109/ICTAI.2012.149⟩
lirmm-00830923v1  Conference papers
Chongsheng ZhangYuan HaoMirjana MazuranCarlo ZanioloHamid Mousavi et al.  Mining frequent itemsets over tuple-evolving data streams
SAC: Symposium on Applied Computing, Mar 2013, Coimbra, Portugal. pp.267-274, ⟨10.1145/2480362.2480419⟩
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tel-00788309v1  Habilitation à diriger des recherches
Florent Masseglia. Extraction de connaissances : réunir volumes de données et motifs significatifs
Base de données [cs.DB]. Université Nice Sophia Antipolis, 2009
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lirmm-02984969v1  Journal articles
Heraldo BorgesMurillo DutraAmin BazazRafaelli CoutinhoFábio Perosi et al.  Spatial-Time Motifs Discovery
Intelligent Data Analysis, IOS Press, 2020
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hal-00789034v1  Journal articles
Alice MarascuFlorent Masseglia. Atypicity Detection in Data Streams: a Self-Adjusting Approach
Intelligent Data Analysis, IOS Press, 2011, 15 (1), pp.89-105. ⟨10.3233/IDA-2010-0457⟩
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hal-00640214v1  Conference papers
François PetitjeanFlorent MassegliaPierre Gançarski. Découverte de motifs d'évolution significatifs dans les séries temporelles d'images satellites
EGC: Extraction et Gestion des Connaissances, Jan 2011, Brest, France. pp.665-676
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hal-00640213v1  Journal articles
Bashar SalehFlorent Masseglia. Discovering Frequent Behaviors: Time is an Essential Element of the Context
Knowledge and Information Systems (KAIS), Springer, 2011, 28 (2), pp.311-331
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lirmm-00639480v1  Journal articles
François PetitjeanFlorent MassegliaPierre GançarskiGermain Forestier. Discovering Significant Evolution Patterns from Satelllite Image Time Series
International Journal of Neural Systems, World Scientific Publishing, 2011, 21 (6), pp.15
lirmm-00653732v1  Conference papers
Chongsheng ZhangFlorent MassegliaYves Lechevallier. ABS: The Anti Bouncing Model for Usage Data Streams
ICDM'10 : The 10th IEEE International Conference on Data Mining, Dec 2010, Sydney, Australia. pp.1169-1174, ⟨10.1109/ICDM.2010.91⟩
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lirmm-03036910v1  Conference papers
Khadidja MeguelatiBenedicte FontezNadine HilgertFlorent MassegliaIsabelle Sanchez. Massively Distributed Clustering via Dirichlet Process Mixture
ECML PKDD 2020 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2020, Ghent (virtual), Belgium
lirmm-00913008v1  Patents
Renaud CezarDino IencoAndré MasFlorent MassegliaPascal Poncelet et al.  Process for identifying rare events
United States, Patent n° : US 20150363551 A1, WO 2014118343 A2, PCT/EP2014/051963. 2014
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lirmm-02364411v1  Conference papers
Khadidja MeguelatiBénédicte FontezNadine HilgertFlorent Masseglia. High Dimensional Data Clustering by means of Distributed Dirichlet Process Mixture Models
IEEE Big Data 2019 - IEEE International Conference on Big Data, Dec 2019, Los-Angeles, United States