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ORCIDFlorent Masseglia
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- affiliation: INRIA, France
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2020 – today
- 2024
[c75]Benoit Lange
, Reza Akbarinia, Florent Masseglia:
A One-Health Platform for Antimicrobial Resistance Data Analytics. CIKM 2024: 5230-5233- 2023
- [j30]Tanmoy Mondal, Reza Akbarinia, Florent Masseglia:
kNN matrix profile for knowledge discovery from time series. Data Min. Knowl. Discov. 37(3): 1055-1089 (2023) - [j29]Lamia Djebour, Reza Akbarinia, Florent Masseglia:
Variable-Size Segmentation for Time Series Representation. Trans. Large Scale Data Knowl. Centered Syst. 53: 34-65 (2023) - [j28]Reza Akbarinia, Christophe Botella, Alexis Joly, Florent Masseglia, Marta Mattoso, Eduardo S. Ogasawara, Daniel de Oliveira, Esther Pacitti, Fábio Porto, Christophe Pradal, Dennis E. Shasha, Patrick Valduriez:
Life Science Workflow Services (LifeSWS): Motivations and Architecture. Trans. Large Scale Data Knowl. Centered Syst. 55: 1-24 (2023) - [i4]Rebecca Salles, Janio Lima, Rafaelli Coutinho, Esther Pacitti, Florent Masseglia, Reza Akbarinia, Chao Chen, Jonathan M. Garibaldi, Fábio Porto, Eduardo S. Ogasawara:
SoftED: Metrics for Soft Evaluation of Time Series Event Detection. CoRR abs/2304.00439 (2023) - 2022
- [c74]Lamia Djebour, Reza Akbarinia, Florent Masseglia:
Parallel Techniques for Variable Size Segmentation of Time Series Datasets. ADBIS 2022: 148-162 - [c73]Lamia Djebour, Reza Akbarinia, Florent Masseglia:
Variable size segmentation for efficient representation and querying of non-uniform time series datasets. SAC 2022: 395-402 - 2021
- [j27]Oleksandra Levchenko, Boyan Kolev, Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas, Dennis E. Shasha, Patrick Valduriez:
BestNeighbor: efficient evaluation of kNN queries on large time series databases. Knowl. Inf. Syst. 63(2): 349-378 (2021) - [j26]Heraldo Borges, Reza Akbarinia, Florent Masseglia:
Anomaly Detection in Time Series. Trans. Large Scale Data Knowl. Centered Syst. 50: 46-62 (2021) - 2020
- [j25]Asma Belhadi, Youcef Djenouri, Kjetil Nørvåg, Heri Ramampiaro, Florent Masseglia, Jerry Chun-Wei Lin:
Space-time series clustering: Algorithms, taxonomy, and case study on urban smart cities. Eng. Appl. Artif. Intell. 95: 103857 (2020) - [j24]Heraldo Borges, Murillo Dutra, Amin Bazaz, Rafaelli Coutinho, Fabio Perosi, Fábio Porto, Florent Masseglia, Esther Pacitti, Eduardo S. Ogasawara:
Spatial-time motifs discovery. Intell. Data Anal. 24(5): 1121-1140 (2020) - [j23]Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas:
Massively Distributed Time Series Indexing and Querying. IEEE Trans. Knowl. Data Eng. 32(1): 108-120 (2020) - [c72]Khadidja Meguelati, Benedicte Fontez, Nadine Hilgert, Florent Masseglia, Isabelle Sanchez:
Massively Distributed Clustering via Dirichlet Process Mixture. ECML/PKDD (5) 2020: 536-540 - [i3]Sara Scaramuccia, Simon Nanty, Florent Masseglia:
Feedback Clustering for Online Travel Agencies Searches: a Case Study. CoRR abs/2007.07073 (2020)
2010 – 2019
- 2019
- [c71]Khadidja Meguelati, Benedicte Fontez, Nadine Hilgert, Florent Masseglia:
High Dimensional Data Clustering by means of Distributed Dirichlet Process Mixture Models. IEEE BigData 2019: 890-899 - [c70]Boyan Kolev, Reza Akbarinia, Ricardo Jiménez-Peris, Oleksandra Levchenko, Florent Masseglia, Marta Patiño, Patrick Valduriez:
Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression Capabilities. CLOSER 2019: 681-687 - [c69]Boyan Kolev, Reza Akbarinia, Ricardo Jiménez-Peris, Oleksandra Levchenko, Florent Masseglia, Marta Patiño, Patrick Valduriez:
Pipelined Implementation of a Parallel Streaming Method for Time Series Correlation Discovery on Sliding Windows. DATA 2019: 431-436 - [c68]Khadidja Meguelati, Benedicte Fontez, Nadine Hilgert, Florent Masseglia:
Massively Distributed Dirichlet Process Mixture Models. INFORSID 2019: 221-222 - [c67]Oleksandra Levchenko, Boyan Kolev, Djamel Edine Yagoubi, Dennis E. Shasha, Themis Palpanas, Patrick Valduriez, Reza Akbarinia, Florent Masseglia:
Distributed Algorithms to Find Similar Time Series. ECML/PKDD (3) 2019: 781-785 - [c66]Khadidja Meguelati, Benedicte Fontez, Nadine Hilgert, Florent Masseglia:
Dirichlet process mixture models made scalable and effective by means of massive distribution. SAC 2019: 502-509 - [i2]Corinne Atlan, Jean-Pierre Archambault, Olivier Banus, Frédéric Bardeau, Amélie Blandeau, Antonin Cois, Martine Courbin, Gérard Giraudon, Saint-Clair Lefèvre, Valérie Letard, Bastien Masse, Florent Masseglia, Benjamin Ninassi, Sophie de Quatrebarbes, Margarida Romero, Didier Roy, Thierry Viéville:
Apprentissage de la pensée informatique : de la formation des enseignant·e·s à la formation de tou·te·s les citoyen·ne·s. CoRR abs/1906.00647 (2019) - 2018
- [j22]Djamel Edine Yagoubi, Reza Akbarinia, Boyan Kolev, Oleksandra Levchenko, Florent Masseglia, Patrick Valduriez, Dennis E. Shasha:
ParCorr: efficient parallel methods to identify similar time series pairs across sliding windows. Data Min. Knowl. Discov. 32(5): 1481-1507 (2018) - [c65]Oleksandra Levchenko, Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Boyan Kolev, Dennis E. Shasha:
Spark-parSketch: A Massively Distributed Indexing of Time Series Datasets. CIKM 2018: 1951-1954 - [c64]Riccardo Campisano, Heraldo Borges, Fábio Porto, Fabio Perosi, Esther Pacitti, Florent Masseglia, Eduardo S. Ogasawara:
Discovering Tight Space-Time Sequences. DaWaK 2018: 247-257 - [c63]Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia:
Maximally informative k-itemset mining from massively distributed data streams. SAC 2018: 502-509 - [c62]Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José J. Camata, Alvaro L. G. A. Coutinho, Daniel Gaspar, Noel Moreno Lemus, Ji Liu, Hermano Lustosa, Florent Masseglia, Fabrício Nogueira da Silva, Vítor Silva, Renan Souza, Kary A. C. S. Ocaña, Eduardo S. Ogasawara, Daniel de Oliveira, Esther Pacitti, Fábio Porto, Dennis E. Shasha:
Scientific Data Analysis Using Data-Intensive Scalable Computing: The SciDISC Project. LADaS@VLDB 2018: 1-8 - [i1]Mohamed Reda Bouadjenek, Esther Pacitti, Maximilien Servajean, Florent Masseglia, Amr El Abbadi:
A Distributed Collaborative Filtering Algorithm Using Multiple Data Sources. CoRR abs/1807.05853 (2018) - 2017
- [j21]Saber Salah, Reza Akbarinia, Florent Masseglia:
A highly scalable parallel algorithm for maximally informative k-itemset mining. Knowl. Inf. Syst. 50(1): 1-26 (2017) - [j20]Saber Salah, Reza Akbarinia, Florent Masseglia:
Data placement in massively distributed environments for fast parallel mining of frequent itemsets. Knowl. Inf. Syst. 53(1): 207-237 (2017) - [c61]Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia:
Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach. CAiSE 2017: 231-246 - [c60]Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Dennis E. Shasha:
RadiusSketch: Massively Distributed Indexing of Time Series. DSAA 2017: 262-271 - [c59]Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas:
DPiSAX: Massively Distributed Partitioned iSAX. ICDM 2017: 1135-1140 - 2016
- [c58]Tristan Allard, Georges Hébrail, Florent Masseglia, Esther Pacitti:
A new privacy-preserving solution for clustering massively distributed personal times-series. ICDE 2016: 1370-1373 - [c57]Riccardo Campisano, Fábio Porto, Esther Pacitti, Florent Masseglia, Eduardo S. Ogasawara:
Spatial Sequential Pattern Mining for Seismic Data. SBBD 2016: 241-246 - 2015
- [c56]Saber Salah, Reza Akbarinia, Florent Masseglia:
Data Partitioning for Fast Mining of Frequent Itemsets in Massively Distributed Environments. DEXA (1) 2015: 303-318 - [c55]Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia:
A Prime Number Based Approach for Closed Frequent Itemset Mining in Big Data. DEXA (1) 2015: 509-516 - [c54]Saber Salah, Reza Akbarinia, Florent Masseglia:
Fast Parallel Mining of Maximally Informative k-Itemsets in Big Data. ICDM 2015: 359-368 - [c53]Saber Salah, Reza Akbarinia, Florent Masseglia:
Optimizing the Data-Process Relationship for Fast Mining of Frequent Itemsets in MapReduce. MLDM 2015: 217-231 - [c52]Reza Akbarinia, Florent Masseglia:
Aggregation-Aware Compression of Probabilistic Streaming Time Series. MLDM 2015: 232-247 - [c51]Tristan Allard, Georges Hébrail, Florent Masseglia, Esther Pacitti:
Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering. SIGMOD Conference 2015: 779-794 - 2014
- [j19]Chongsheng Zhang, Florent Masseglia, Yves Lechevallier:
The anti-bouncing data stream model for web usage streams with intralinkings. Inf. Sci. 278: 757-772 (2014) - [j18]Wei Wang, Thomas Guyet, René Quiniou, Marie-Odile Cordier, Florent Masseglia, Xiangliang Zhang:
Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks. Knowl. Based Syst. 70: 103-117 (2014) - 2013
- [c50]Enikö Székely, Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire, Renaud Cezar:
A Density-Based Backward Approach to Isolate Rare Events in Large-Scale Applications. Discovery Science 2013: 249-264 - [c49]Reza Akbarinia, Florent Masseglia:
Fast and Exact Mining of Probabilistic Data Streams. ECML/PKDD (1) 2013: 493-508 - [c48]Chongsheng Zhang, Yuan Hao, Mirjana Mazuran, Carlo Zaniolo, Hamid Mousavi, Florent Masseglia:
Mining frequent itemsets over tuple-evolving data streams. SAC 2013: 267-274 - 2012
- [c47]Chongsheng Zhang, Florent Masseglia, Xiangliang Zhang:
Discovering Highly Informative Feature Set over High Dimensions. ICTAI 2012: 1059-1064 - [c46]Chongsheng Zhang, Florent Masseglia, Xiangliang Zhang:
Modeling and Clustering Users with Evolving Profiles in Usage Streams. TIME 2012: 133-140 - 2011
- [j17]Alice Marascu, Florent Masseglia:
Atypicity detection in data streams: A self-adjusting approach. Intell. Data Anal. 15(1): 89-105 (2011) - [j16]François Petitjean, Florent Masseglia, Pierre Gançarski, Germain Forestier:
Discovering Significant Evolution Patterns from Satellite Image Time Series. Int. J. Neural Syst. 21(6): 475-489 (2011) - [j15]Bashar Saleh, Florent Masseglia:
Discovering frequent behaviors: time is an essential element of the context. Knowl. Inf. Syst. 28(2): 311-331 (2011) - [c45]François Petitjean, Florent Masseglia, Pierre Gançarski:
Découverte de motifs d'évolutions significatifs dans les séries temporelles d'images satellites. EGC 2011: 665-676 - 2010
- [c44]Chongsheng Zhang, Florent Masseglia:
Discovering Highly Informative Feature Sets from Data Streams. DEXA (1) 2010: 91-104 - [c43]Chongsheng Zhang, Florent Masseglia:
Extraction d'itemsets distinctifs dans les flux de données. EGC 2010: 187-198 - [c42]Alice Marascu, Florent Masseglia, Yves Lechevallier:
REGLO : une nouvelle stratégie pour résumer un flux de séries temporelles. EGC 2010: 217-228 - [c41]Chongsheng Zhang, Florent Masseglia, Yves Lechevallier:
ABS: The Anti Bouncing Model for Usage Data Streams. ICDM 2010: 1169-1174 - [c40]François Petitjean, Pierre Gançarski, Florent Masseglia, Germain Forestier:
Analysing Satellite Image Time Series by Means of Pattern Mining. IDEAL 2010: 45-52 - [c39]Alice Marascu, Florent Masseglia, Yves Lechevallier:
A fast approximation strategy for summarizing a set of streaming time series. SAC 2010: 1617-1621
2000 – 2009
- 2009
- [b1]Florent Masseglia:
Extraction de connaissances : réunir volumes de données et motifs significatifs. University of Nice Sophia Antipolis, France, 2009 - [j14]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Efficient mining of sequential patterns with time constraints: Reducing the combinations. Expert Syst. Appl. 36(2): 2677-2690 (2009) - [j13]Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire:
Evolution patterns and gradual trends. Int. J. Intell. Syst. 24(10): 1013-1038 (2009) - [c38]François Trousset, Pascal Poncelet, Florent Masseglia:
SAX: a privacy preserving general pupose methodapplied to detection of intrusions. CIKM-PAVLAD 2009: 17-24 - [c37]Goverdhan Singh, Florent Masseglia, Céline Fiot, Alice Marascu, Pascal Poncelet:
Mining Common Outliers for Intrusion Detection. EGC (best of volume) 2009: 217-234 - [c36]Nischal Verma, François Trousset, Pascal Poncelet, Florent Masseglia:
Intrusion Detections in Collaborative Organizations by Preserving Privacy. EGC (best of volume) 2009: 235-247 - [c35]Nischal Verma, François Trousset, Pascal Poncelet, Florent Masseglia:
Détection d'intrusions dans un environnement collaboratif sécurisé. EGC 2009: 301-312 - [c34]Goverdhan Singh, Florent Masseglia, Céline Fiot, Alice Marascu, Pascal Poncelet:
Collaborative Outlier Mining for Intrusion Detection. EGC 2009: 313-324 - [c33]Alice Marascu, Florent Masseglia:
Détection d'enregistrements atypiques dans un flot de données: une approche multi-résolution. EGC 2009: 455-456 - [c32]Wei Wang, Thomas Guyet, Rene Quiniou, Marie-Odile Cordier, Florent Masseglia:
Online and adaptive anomaly Detection: detecting intrusions in unlabelled audit data streams. EGC 2009: 457-458 - [c31]Goverdhan Singh, Florent Masseglia, Céline Fiot, Alice Marascu, Pascal Poncelet:
Data Mining for Intrusion Detection: From Outliers to True Intrusions. PAKDD 2009: 891-898 - [c30]Alice Marascu, Florent Masseglia:
A Multi-resolution Approach for Atypical Behaviour Mining. PAKDD 2009: 899-906 - [c29]Alice Marascu, Florent Masseglia:
Parameterless outlier detection in data streams. SAC 2009: 1491-1495 - [c28]Wei Wang, Florent Masseglia, Thomas Guyet, Rene Quiniou, Marie-Odile Cordier:
A general framework for adaptive and online detection of web attacks. WWW 2009: 1141-1142 - [r1]Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet:
Sequential Pattern Mining. Encyclopedia of Data Warehousing and Mining 2009: 1800-1805 - 2008
- [j12]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire, Alice Marascu:
Web usage mining: extracting unexpected periods from web logs. Data Min. Knowl. Discov. 16(1): 39-65 (2008) - [j11]Zhongfei Zhang, Florent Masseglia, Ramesh C. Jain, Alberto Del Bimbo:
Editorial: Introduction to the Special Issue on Multimedia Data Mining. IEEE Trans. Multim. 10(2): 165-166 (2008) - [c27]Bashar Saleh, Florent Masseglia:
Extraction d'itemsets compacts. EGC 2008: 409-414 - [c26]Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire:
TED and EVA: Expressing temporal tendencies among quantitative variables using fuzzy sequential patterns. FUZZ-IEEE 2008: 1861-1868 - [c25]Céline Fiot, Florent Masseglia, Anne Laurent, Maguelonne Teisseire:
Des séquences aux tendances. INFORSID 2008 - [c24]Bashar Saleh, Florent Masseglia:
Time Aware Mining of Itemsets. TIME 2008: 93-97 - 2007
- [j10]Alice Marascu, Florent Masseglia:
Mining sequential patterns from data streams: a centroid approach. Monde des Util. Anal. Données 36: 42-60 (2007) - 2006
- [j9]Alice Marascu, Florent Masseglia:
Mining sequential patterns from data streams: a centroid approach. J. Intell. Inf. Syst. 27(3): 291-307 (2006) - [j8]Omar Boussaid, Pierre Gançarski, Florent Masseglia, Brigitte Trousse, Dominique Desbois:
Notes de lecture : Fouille de Données Complexes. Monde des Util. Anal. Données 34: 117-118 (2006) - [j7]Zhongfei Zhang, Florent Masseglia, Ramesh C. Jain, Alberto Del Bimbo:
KDD/MDM 2006: The 7th KDD Multimedia Data Mining workshop report. SIGKDD Explor. 8(2): 92-95 (2006) - [c23]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Peer-to-Peer Usage Analysis: a Distributed Mining Approach. AINA (1) 2006: 993-998 - [c22]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire, Alice Marascu:
Web Usage Mining : extraction de périodes denses à partir des logs. EGC 2006: 403-408 - [c21]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Fouille de données dans les systèmes Pair-à-Pair pour améliorer la recherche de ressources. EGC 2006: 469-474 - [c20]Alice Marascu, Florent Masseglia:
Extraction de motifs séquentiels dans les flots de données d'usage du Web. EGC 2006: 627-638 - [c19]Alice Marascu, Florent Masseglia:
Une approche centroïde pour la classification de séquences dans les data streams. INFORSID 2006: 751-765 - [c18]Doru Tanasa, Florent Masseglia, Brigitte Trousse:
GWUM : une généralisation des pages Web guidée par les usages. INFORSID 2006: 783-798 - 2005
- [j6]Fatma Bouali, Latifur Khan, Florent Masseglia:
The 6th international workshop on Multimedia Data Mining (MDM/KDD2005). SIGKDD Explor. 7(2): 148-150 (2005) - [c17]Calin Garboni, Florent Masseglia, Brigitte Trousse:
Sequential Pattern Mining for Structure-Based XML Document Classification. INEX 2005: 458-468 - [e1]Fatma Bouali, Latifur Khan, Florent Masseglia:
Proceedings of the 6th international workshop on Multimedia data mining - mining integrated media and complex data, MDM 2005, Chicago, Illinois, USA, August 21, 2005. ACM 2005 [contents] - 2004
- [j5]Florent Masseglia, Doru Tanasa, Brigitte Trousse:
Diviser pour découvrir. Une méthode d'analyse du comportement de tous les utilisateurs d'un site web. Ingénierie des Systèmes d Inf. 9(1): 61-83 (2004) - [j4]Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet:
Extraction de motifs séquentiels. Problèmes et méthodes. Ingénierie des Systèmes d Inf. 9(3-4): 183-210 (2004) - [c16]Florent Masseglia, Doru Tanasa, Brigitte Trousse:
Web Usage Mining: Sequential Pattern Extraction with a Very Low Support. APWeb 2004: 513-522 - [c15]Doru Tanasa, Brigitte Trousse, Florent Masseglia:
Classer pour découvrir : une nouvelle méthode d'analyse du comportement de tous les utilisateurs d'un site web. EGC 2004: 549-560 - [c14]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Pre-Processing Time Constraints for Efficiently Mining Generalized Sequential Patterns. TIME 2004: 87-95 - 2003
- [j3]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Incremental mining of sequential patterns in large databases. Data Knowl. Eng. 46(1): 97-121 (2003) - [j2]Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet:
HDM: A Client/Server/Engine Architecture for Real-Time Web Usage Mining. Knowl. Inf. Syst. 5(4): 439-465 (2003) - [c13]Florent Masseglia, Doru Tanasa, Brigitte Trousse:
Diviser pour Découvrir : une Méthode d'Analyse du Comportement de Tous les Utilisateurs d'un Site Web. BDA 2003 - 2002
- [c12]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
HDM, un module de fouille de données distribué et temps réel. EGC 2002: 393-398 - [c11]Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet:
Real Time Web Usage Mining with a Distributed Navigation Analysis. RIDE 2002: 169- - 2001
- [c10]Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet:
Web Usage Mining Inter-Sites: Analyse du comportement des utilisateurs à impact immédiat. BDA 2001 - [c9]Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet:
Real-Time Web Usage Mining: A Heuristic Based Distributed Miner. WISE (1) 2001: 288-300 - 2000
- [c8]Pierre-Alain Laur, Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
A General Architecture for Finding Structural Regularities on the Web. AIMSA 2000: 179-188 - [c7]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Incremental Mining of Sequential Patterns in Large Databases. BDA 2000 - [c6]Pierre-Alain Laur, Florent Masseglia, Pascal Poncelet:
Schema Mining: Finding Structural Regularity among Semistructured Data. PKDD 2000: 498-503 - [c5]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Web Usage Mining: How to Efficiently Manage New Transactions and New Clients. PKDD 2000: 530-535
1990 – 1999
- 1999
- [j1]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Using data mining techniques on Web access logs to dynamically improve hypertext structure. SIGWEB Newsl. 8(3): 13-19 (1999) - [c4]Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
Extraction efficace de motifs séquentiels : le prétraitement des données. Proc. 15èmes Journées Bases de Données Avancées, BDA 1999: 341-360 - [c3]Florent Masseglia, Pascal Poncelet, Rosine Cicchetti:
WebTool: An Integrated Framework for Data Mining. DEXA 1999: 892-901 - [c2]Florent Masseglia, Pascal Poncelet, Rosine Cicchetti:
Webtool: un environnement intégré de data mining. INFORSID 1999: 393-411 - 1998
- [c1]Florent Masseglia, Fabienne Cathala, Pascal Poncelet:
The PSP Approach for Mining Sequential Patterns. PKDD 1998: 176-184
Coauthor Index
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