Number of documents

94

Florent Masseglia


Journal articles19 documents

Conference papers59 documents

  • Khadidja Meguelati, Bénédicte Fontez, Nadine Hilgert, Florent Masseglia. Dirichlet Process Mixture Models made Scalable and Effective by means of Massive Distribution. SAC: Symposium on Applied Computing, Apr 2019, Limassol, Cyprus. ⟨10.1145/3297280.3297327⟩. ⟨hal-01999453⟩
  • Corinne Atlan, Jean-Pierre Archambault, Olivier Banus, Frédéric Bardeau, Amélie Blandeau, et al.. Apprentissage de la pensée informatique : de la formation des enseignant·e·s à la formation de tou·te·s les citoyen·ne·s. EIAH'19 Wokshop : Apprentissage de la pensée informatique de la maternelle à l’Université : retours d’expériences et passage à l’échelle, Jun 2019, Paris, France. ⟨hal-02145480⟩
  • Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia. Maximally Informative k-Itemset Mining from Massively Distributed Data Streams. SAC: Symposium on Applied Computing, Apr 2018, Pau, France. pp.1-10. ⟨hal-01711990⟩
  • Mohamed Bouadjenek, Esther Pacitti, Maximilien Servajean, Florent Masseglia, Amr Abbadi. A Distributed Collaborative Filtering Algorithm Using Multiple Data Sources. DBKDA: Advances in Databases, Knowledge, and Data Applications, May 2018, Nice, France. ⟨hal-01911684⟩
  • Riccardo Campisano, Heraldo Borges, Fábio Porto, Fabio Perosi, Esther Pacitti, et al.. Discovering Tight Space-Time Sequences. DaWaK: Data Warehousing and Knowledge Discovery, Sep 2018, Regensburg, Germany. pp.247-257, ⟨10.1007/978-3-319-98539-8_19⟩. ⟨hal-01925965⟩
  • Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José Camata, et al.. Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project. LADaS: Latin America Data Science Workshop, Aug 2018, Rio de Janeiro, Brazil. ⟨lirmm-01867804⟩
  • Oleksandra Levchenko, Djamel-Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Boyan Kolev, et al.. Spark-parSketch: A Massively Distributed Indexing of Time Series Datasets. CIKM: Conference on Information and Knowledge Management, Oct 2018, Turin, Italy. pp.1951-1954, ⟨10.1145/3269206.3269226⟩. ⟨lirmm-01886760⟩
  • Djamel-Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas. DPiSAX: Massively Distributed Partitioned iSAX. ICDM: International Conference on Data Mining, Nov 2017, New Orleans, United States. pp.1-6, ⟨10.1109/ICDM.2017.151⟩. ⟨lirmm-01620125⟩
  • Djamel-Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Dennis Shasha. RadiusSketch: Massively Distributed Indexing of Time Series. DSAA: Data Science and Advanced Analytics, Oct 2017, Tokyo, Japan. pp.1-10. ⟨lirmm-01620154⟩
  • Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia. Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach. CAiSE: Advanced Information Systems Engineering, Jun 2017, Essen, Germany. pp.231-246, ⟨10.1007/978-3-319-59536-8_15⟩. ⟨lirmm-01620238⟩
  • Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia. Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach. BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. pp.1-15. ⟨lirmm-01620354⟩
  • Saber Salah, Reza Akbarinia, Florent Masseglia. Mining Maximally Informative k-Itemsets in Massively Distributed Environments. BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2016, Poitiers, France. ⟨lirmm-01411190⟩
  • Tristan Allard, Georges Hébrail, Florent Masseglia, Esther Pacitti. A New Privacy-Preserving Solution for Clustering Massively Distributed Personal Times-Series. ICDE: International Conference on Data Engineering, May 2016, Helsinki, Finland. ⟨lirmm-01270268⟩
  • Tristan Allard, Georges Hébrail, Florent Masseglia, Esther Pacitti. Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering. ACM SIGMOD, May 2015, Melbourne, Australia. pp.779-794, ⟨10.1145/2723372.2749453⟩. ⟨hal-01136686⟩
  • Reza Akbarinia, Florent Masseglia. Aggregation-Aware Compression of Probabilistic Streaming Time Series. MLDM: Machine Learning and Data Mining, Jul 2015, Hamburg, Germany. pp.232-247, ⟨10.1007/978-3-319-21024-7_16⟩. ⟨lirmm-01162366⟩
  • Saber Salah, Reza Akbarinia, Florent Masseglia. Fast Parallel Mining of Maximally Informative k-Itemsets in Big Data. ICDM: International Conference on Data Mining, Aug 2015, Atlantic city, United States. pp.359-368, ⟨10.1109/ICDM.2015.86⟩. ⟨lirmm-01187275⟩
  • Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia. A Prime Number Based Approach for Closed Frequent Itemset Mining in Big Data. DEXA: Database and Expert Systems Applications, Sep 2015, Valencia, Spain. pp.509-516, ⟨10.1007/978-3-319-22849-5_35⟩. ⟨lirmm-01169606⟩
  • Saber Salah, Reza Akbarinia, Florent Masseglia. Data Partitioning for Fast Mining of Frequent Itemsets in Massively Distributed Environments. DEXA: Database and Expert Systems Applications, Sep 2015, Valencia, Spain. ⟨lirmm-01169603⟩
  • Saber Salah, Reza Akbarinia, Florent Masseglia. Optimizing the Data-Process Relationship for Fast Mining of Frequent Itemsets in MapReduce. MLDM: Machine Learning and Data Mining, Jul 2015, Hamburg, Germany. pp.217-231, ⟨10.1007/978-3-319-21024-7_15⟩. ⟨lirmm-01171555⟩
  • Marie Duflot, Martin Quinson, Florent Masseglia, Didier Roy, Julien Vaubourg, et al.. When sharing computer science with everyone also helps avoiding digital prejudices.: Escape computer dirty magic: learn Scratch !. Scratch2015AMS, Aug 2015, Amsterdam, Netherlands. ⟨hal-01154767⟩
  • Reza Akbarinia, Florent Masseglia. Compression de flux de données probabilistes attentive à l'agrégation. BDA: Gestion de Données — Principes, Technologies et Applications, Oct 2014, Autrans, France. ⟨lirmm-01091870⟩
  • Reza Akbarinia, Florent Masseglia. Fast and Exact Mining of Probabilistic Data Streams. ECML-PKDD: Machine Learning and Knowledge Discovery in Databases, Sep 2013, Prague, Czech Republic. pp.493-508, ⟨10.1007/978-3-642-40988-2_32⟩. ⟨lirmm-00838618⟩
  • Enikö Székely, Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire, Renaud Cezar. A Density-Based Backward Approach to Isolate Rare Events in Large-Scale Applications. DS: Discovery Science, Oct 2013, Singapore, Singapore. pp.249-264, ⟨10.1007/978-3-642-40897-7_17⟩. ⟨lirmm-00907893⟩
  • Chongsheng Zhang, Yuan Hao, Mirjana Mazuran, Carlo Zaniolo, Hamid 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⟩. ⟨lirmm-00830923⟩
  • Reza Akbarinia, Florent Masseglia. FMU: Fast Mining of Probabilistic Frequent Itemsets in Uncertain Data Streams. BDA: Bases de Données Avancées, 2012, Clermont-Ferrand, France. ⟨lirmm-00748605⟩
  • Chongsheng Zhang, Florent Masseglia, Xiangliang 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. ⟨lirmm-00753791⟩
  • Chongsheng Zhang, Florent Masseglia, Xiangliang 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-00753807⟩
  • François Petitjean, Florent Masseglia, Pierre Gancarski. Découverte de motifs d'évolution significatifs dans les séries temporelles d'images satellites. EGC'11 : 11ème Conférence Internationale Francophone sur l'Extraction et la Gestion des Connaissances, Jan 2011, Brest, France. ⟨hal-00640214⟩
  • Alice Marascu, Florent Masseglia, Yves Lechevallier. A Fast Approximation Strategy for Summarizing a Set of Streaming Time Series. ACM Symposium on Applied Computing, Mar 2010, Sierre, Switzerland. ⟨inria-00461781⟩
  • Alice Marascu, Florent Masseglia, Yves Lechevallier. REGLO: une nouvelle stratégie pour résumer un flux de séries temporelles. Extraction et Gestion des Connaissances, Jan 2010, Hammamet, Tunisie. ⟨inria-00461834⟩
  • Chongsheng Zhang, Florent Masseglia, Yves 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⟩. ⟨lirmm-00653732⟩
  • Chongsheng Zhang, Florent Masseglia. Extraction d'itemsets distinctifs dans les flux de données. Extraction et gestion des connaissances, Jan 2010, France. pp.187-198. ⟨hal-00504877⟩
  • Goverdhan Singh, Florent Masseglia, Céline Fiot, Alice Marascu, Pascal Poncelet. Collaborative Outlier Mining for Intrusion Detection. EGC: Extraction et Gestion des Connaissances, Jan 2009, Strasbourg, France. pp.313-323. ⟨lirmm-00345574⟩
  • Nischal Verma, François Trousset, Pascal Poncelet, Florent Masseglia. Détection d'intrusions dans un environnement collaboratif sécurisé. EGC: Extraction et Gestion des Connaissances, Jan 2009, Strasbourg, France. pp.301-312. ⟨lirmm-00345566⟩
  • Alice Marascu, Florent Masseglia. A Multi-Resolution Approach for Atypical Behaviour Mining. Pacific-Asia Conference on Knowledge Discovery and Data Mining, Apr 2009, Bangkok, Thailand. pp.899-906, ⟨10.1007/978-3-642-01307-2⟩. ⟨inria-00461831⟩
  • Alice Marascu, Florent Masseglia. Détection d'enregistrements atypiques dans un flot de données: une approche multi-résolution. Extraction et Gestion des Connaissances, Jan 2009, Strasbourg, France. ⟨inria-00461838⟩
  • Alice Marascu, Florent Masseglia. Parameterless Outlier Detection in Data Streams. ACM symposium on Applied Computing, Mar 2009, Honolulu, United States. pp.1491-1495. ⟨inria-00461827⟩
  • François Trousset, Pascal Poncelet, Florent Masseglia. SAX: A Privacy Preserving General Purpose Method applied to Detection of Intrusions. ACM First International Workshop on Privacy and Anonymity for Very Large Datasets, join with CIKM 09, Nov 2009, Hong Kong, China. pp.17-24. ⟨lirmm-00430646⟩
  • Wei Wang, Florent Masseglia, Thomas Guyet, René Quiniou, Marie-Odile Cordier. A General Framework for Adaptive and Online Detection of Web attacks. 18th International World Wide Web Conference - WWW 2009, Apr 2009, Madrid, Spain. ⟨inria-00461391⟩
  • Wei Wang, Thomas Guyet, René Quiniou, Marie-Odile Cordier, Florent Masseglia, et al.. Online and Adaptive anomaly Detection: detecting intrusions in unlabelled audit data streams. EGC 2009, 2009, Strasbourg, France. ⟨inria-00460723⟩
  • Goverdhan Singh, Florent Masseglia, Céline Fiot, Alice Marascu, Pascal Poncelet. Data Mining for Intrusion Detection: from Outliers to True Intrusions. The 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09), Apr 2009, Bankok, Thailand. pp.891-898, ⟨10.1007/978-3-642-01307-2_93⟩. ⟨inria-00359206v2⟩
  • Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet. Real Time Web Usage Mining with a Distributed Navigation Analysis. RIDE'02: International Workshop on Research Issues on Data Engineering, San Jose, USA, pp.6. ⟨lirmm-00268631⟩
  • Bashar Saleh, Florent Masseglia. Time Aware Mining of Itemsets. TIME, Jun 2008, Montreal, Canada. pp.93-97, ⟨10.1109/TIME.2008.12⟩. ⟨inria-00359182⟩
  • Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet. HDM, un Module de Fouille de Données Distribué et Temps Réel. EGC'02: Extraction et Gestion des Connaissances, pp.393-398. ⟨lirmm-00268518⟩
  • Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire. Des séquences aux tendances. INFORSID'08 : XXVIème Congrès Informatique des Organisations et Systèmes d'Information et de Décision, France. pp.16. ⟨lirmm-00273920⟩
  • Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire. TED and EVA : Expressing Temporal Tendencies Among Quantitative Variables Using Fuzzy Sequential Patterns. WCCI408: IEEE World Congress on Computational Intelligence (Fuzz-IEEE'08: IEEE International Conference on Fuzzy Sets and Systems), France. pp.8. ⟨lirmm-00273907⟩
  • Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire. Gradual Trends in Fuzzy Sequential Patterns. IPMU'08: Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2008, Malaga, Spain. pp.N/A. ⟨lirmm-00273910⟩
  • Alice Marascu, Florent Masseglia. Limites d'une approche incrémentale pour la segmentation de séquences dans les flux. Fouille de données complexes dans un processus d'extraction de connaissances, Jan 2007, Namur, Belgique. ⟨inria-00461878⟩
  • Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire. Peer-to-Peer Usage Analysis: a Distributed Mining Approach. AINA: Advanced Information Networking and Applications, 2006, Vienna, Austria. ⟨hal-00106798⟩
  • Alice Marascu, Florent Masseglia. Extraction de motifs séquentiels dans les flots de données d'usage du Web. Extraction et Gestion des Connaissances, Jan 2006, Lille, France. pp.627-638. ⟨inria-00461841⟩
  • Alice Marascu, Florent Masseglia. Classification de flots de séquences basée sur une approche centroïde. INFORSID, Informatique des organisations et systèmes d'information et de décision, Jun 2006, Hammamet, Tunisie. ⟨inria-00461839⟩
  • Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire, Alice Marascu. Usage Mining : extraction de périodes denses à partir des logs. Extraction et Gestion des Connaissances, Jan 2006, Lille, France. ⟨inria-00461840⟩
  • Alice Marascu, Florent Masseglia. Classification de flots de séquences basée sur une approche centroïde. Fouille de données complexes dans un processus d'extraction de connaissances, Jan 2006, Lille, France. pp.131-139. ⟨inria-00461880⟩
  • Alice Marascu, Florent Masseglia. Mining Sequential Patterns from Temporal Streaming Data. First ECML/PKDD Workshop on Mining Spatio-Temporal Data (MSTD'05), held in conjunction with the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'05), Nov 2005, Porto, Portugal. ⟨inria-00461843⟩
  • Alice Marascu, Florent Masseglia. Mining Data Streams for Frequent Sequences Extraction. IEEE first Workshop on Mining Complex Data (MCD'05). Held in conjunction with ICDM'05, Nov 2005, Houston, United States. ⟨inria-00461876⟩
  • Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire, Alice Marascu. Web Usage Mining: Extracting Unexpected Periods from Web Logs. IEEE 2nd Workshop on Temporal Data Mining (TDM'05). Held in conjunction with ICDM'05, Nov 2005, Houston, United States. ⟨inria-00461877⟩
  • Florent Masseglia, Doru Tanasa, Brigitte Trousse. Web Usage Mining: Sequential Pattern Extraction with a Very Low Support. Advanced Web Technologies and Applications: 6th Asia-Pacific Web Conference, APWeb 2004, Apr 2004, Hangzhou, China. pp.513--522, ⟨10.1007/978-3-540-24655-8_56⟩. ⟨hal-00950768⟩
  • Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet. Pre-Processing Time Constraints for Efficiently Mining Generalized Sequential Patterns. TIME'04: 11th International Symposium on Temporal Representation and Reasoning, Jul 2004, Tatihou, Basse-Normandie (France), pp.87-95. ⟨lirmm-00108888⟩
  • Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire. Web Usage Mining: How to Efficiently Manage New transactions and New Customers. 4th European Conference on Principles of Data Mining and Knowledge Discovery, 2000, Lyon, France. ⟨hal-00008926⟩

Poster communications1 document

  • Boyan Kolev, Oleksandra Levchenko, Florent Masseglia, Reza Akbarinia, Esther Pacitti, et al.. Highly Scalable Real-Time Analytics with CloudDBAppliance. XLDB: Extremely Large Databases Conference, Oct 2017, Clermont-Ferrand, France. 10th Extremely Large Databases Conference, 2017, ⟨https://xldb2017.uca.fr⟩. ⟨lirmm-01632355⟩

Books2 documents

  • Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire. Data Mining Patterns: New Methods and Applications. IDEA Group, pp.307, 2007, 13 978-1599041629. ⟨lirmm-00365419⟩
  • Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire. Successes and New Directions in Data Mining. IDEA Group, pp.1-369, 2007, 13 978-1599046457. ⟨lirmm-00365422⟩

Book sections4 documents

  • Goverdhan Singh, Florent Masseglia, Céline Fiot, Alice Marascu, Pascal Poncelet. Mining Common Outliers for Intrusion Detection. Fabrice Guillet; Gilbert Ritschard; Djamel Abdelkader Zighed; Henri Briand. Advances in Knowledge Discovery and Management, 292, Springer, pp.217-234, 2010, Studies in Computational Intelligence, 978-3-642-00579-4. ⟨10.1007/978-3-642-00580-0_13⟩. ⟨lirmm-00798705⟩
  • Verma Nischal, François Trousset, Pascal Poncelet, Florent Masseglia. Intrusion Detections in Collaborative Organizations by Preserving Privacy. Fabrice Guillet and Gilbert Ritschard and Djamel Abdelkader Zighed and Henri Briand. Advances in Knowledge Discovery and Management, 292, Springer, pp.235-247, 2010, Studies in Computational Intelligence, 978-3-642-00579-4. ⟨10.1007/978-3-642-00580-0_14⟩. ⟨lirmm-00430642⟩
  • Brigitte Trousse, Marie-Aude Aufaure, Bénédicte Le Grand, Yves Lechevallier, Florent Masseglia. Web Usage Mining for Ontology Management. Data Mining with Ontologies: Implementation, Findings and Framework, Idea Group Publishing, pp.37-64, 2007. ⟨hal-00256574⟩
  • Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet. Sequential Pattern Mining. John Wang. Encyclopedia of Data Warehousing and Mining, Idea Group Reference, pp.1028-1032, 2005, 1-59140-557-2. ⟨lirmm-00106576⟩

Patents2 documents

  • Tristan Allard, Georges Hébrail, Florent Masseglia, Esther Pacitti. Procédé et installation de comparaison de consommation d'effluents sans divulgation de données de consommations mesurées . France, N° de brevet: EP 2930471 A1. 2015. ⟨hal-01274207⟩
  • Renaud Cezar, Dino Ienco, André Mas, Florent Masseglia, Pascal Poncelet, et al.. Process for identifying rare events. United States, Patent n° : US 20150363551 A1, WO 2014118343 A2, PCT/EP2014/051963. 2014. ⟨lirmm-00913008⟩

Other publications1 document

  • Thierry Vieville, Sylvie Boldo, Florent Masseglia, Pierre Bernhard. « Structures : organisation, complexité, dynamique » des mot-clés au sens inattendu. 2015. ⟨hal-01238442⟩

Reports3 documents

  • Enikö Székely, Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire, Renaud Cezar. Isolating rare events in large-scale applications using a backward approach. [Research Report] RR-13003, LIRMM. 2013. ⟨lirmm-00798074⟩
  • Antoine Rousseau, Aurélie Darnaud, Brice Goglin, Céline Acharian, Christine Leininger, et al.. Médiation Scientifique : une facette de nos métiers de la recherche. [Interne] none. 2013, pp.34. ⟨hal-00804915⟩
  • Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire. TED and EVA: Expressing Temporal Tendencies among Quantitative Variables using Fuzzy Sequential Patterns. RR-08002, 2008. ⟨lirmm-00258079⟩

Habilitation à diriger des recherches1 document

  • Florent Masseglia. Extraction de connaissances : réunir volumes de données et motifs significatifs. Base de données [cs.DB]. Université Nice Sophia Antipolis, 2009. ⟨tel-00788309⟩

Software2 documents

  • Oleksandra Levchenko, Djamel-Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Boyan Kolev, et al.. Imitates. 2019. ⟨hal-02095640⟩
  • Florent Masseglia, Julien Diener. LogMagnet. 2019. ⟨hal-02098365⟩