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Florent Masseglia: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Pierre-Alain Laur, Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    A General Architecture for Finding Structural Regularities on the Web. [Citation Graph (0, 0)][DBLP]
    AIMSA, 2000, pp:179-188 [Conf]
  2. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Peer-to-Peer Usage Analysis: a Distributed Mining Approach. [Citation Graph (0, 0)][DBLP]
    AINA (1), 2006, pp:993-998 [Conf]
  3. Florent Masseglia, Doru Tanasa, Brigitte Trousse
    Web Usage Mining: Sequential Pattern Extraction with a Very Low Support. [Citation Graph (0, 0)][DBLP]
    APWeb, 2004, pp:513-522 [Conf]
  4. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Incremental Mining of Sequential Patterns in Large Databases. [Citation Graph (0, 0)][DBLP]
    BDA, 2000, pp:- [Conf]
  5. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Extraction efficace de motifs séquentiels : le prétraitement des données. [Citation Graph (0, 0)][DBLP]
    Proc. 15èmes Journées Bases de Données Avancées, BDA, 1999, pp:341-360 [Conf]
  6. Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet
    Web Usage Mining Inter-Sites: Analyse du comportement des utilisateurs à impact immédiat. [Citation Graph (0, 0)][DBLP]
    BDA, 2001, pp:- [Conf]
  7. Florent Masseglia, Doru Tanasa, Brigitte Trousse
    Diviser pour Découvrir : une Méthode d'Analyse du Comportement de Tous les Utilisateurs d'un Site Web. [Citation Graph (0, 0)][DBLP]
    BDA, 2003, pp:- [Conf]
  8. Florent Masseglia, Pascal Poncelet, Rosine Cicchetti
    WebTool: An Integrated Framework for Data Mining. [Citation Graph (0, 0)][DBLP]
    DEXA, 1999, pp:892-901 [Conf]
  9. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire, Alice Marascu
    Web Usage Mining : extraction de périodes denses à partir des logs. [Citation Graph (0, 0)][DBLP]
    EGC, 2006, pp:403-408 [Conf]
  10. Alice Marascu, Florent Masseglia
    Extraction de motifs séquentiels dans les flots de données d'usage du Web. [Citation Graph (0, 0)][DBLP]
    EGC, 2006, pp:627-638 [Conf]
  11. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    HDM, un module de fouille de données distribué et temps réel. [Citation Graph (0, 0)][DBLP]
    EGC, 2002, pp:393-398 [Conf]
  12. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Fouille de données dans les systèmes Pair-à-Pair pour améliorer la recherche de ressources. [Citation Graph (0, 0)][DBLP]
    EGC, 2006, pp:469-474 [Conf]
  13. Doru Tanasa, Brigitte Trousse, Florent Masseglia
    Classer pour découvrir : une nouvelle méthode d'analyse du comportement de tous les utilisateurs d'un site web. [Citation Graph (0, 0)][DBLP]
    EGC, 2004, pp:549-560 [Conf]
  14. Calin Garboni, Florent Masseglia, Brigitte Trousse
    Sequential Pattern Mining for Structure-Based XML Document Classification. [Citation Graph (0, 0)][DBLP]
    INEX, 2005, pp:458-468 [Conf]
  15. Alice Marascu, Florent Masseglia
    Une approche centroïde pour la classification de séquences dans les data streams. [Citation Graph (0, 0)][DBLP]
    INFORSID, 2006, pp:751-765 [Conf]
  16. Florent Masseglia, Pascal Poncelet, Rosine Cicchetti
    Webtool: un environnement intégré de data mining. [Citation Graph (0, 0)][DBLP]
    INFORSID, 1999, pp:393-411 [Conf]
  17. Doru Tanasa, Florent Masseglia, Brigitte Trousse
    GWUM : une généralisation des pages Web guidée par les usages. [Citation Graph (0, 0)][DBLP]
    INFORSID, 2006, pp:783-798 [Conf]
  18. Florent Masseglia, Fabienne Cathala, Pascal Poncelet
    The PSP Approach for Mining Sequential Patterns. [Citation Graph (0, 0)][DBLP]
    PKDD, 1998, pp:176-184 [Conf]
  19. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Web Usage Mining: How to Efficiently Manage New Transactions and New Clients. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:530-535 [Conf]
  20. Pierre-Alain Laur, Florent Masseglia, Pascal Poncelet
    Schema Mining: Finding Structural Regularity among Semistructured Data. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:498-503 [Conf]
  21. Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet
    Real Time Web Usage Mining with a Distributed Navigation Analysis. [Citation Graph (0, 0)][DBLP]
    RIDE, 2002, pp:169-0 [Conf]
  22. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Pre-Processing Time Constraints for Efficiently Mining Generalized Sequential Patterns. [Citation Graph (0, 0)][DBLP]
    TIME, 2004, pp:87-95 [Conf]
  23. Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet
    Real-Time Web Usage Mining: A Heuristic Based Distributed Miner. [Citation Graph (0, 0)][DBLP]
    WISE (1), 2001, pp:288-0 [Conf]
  24. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Incremental mining of sequential patterns in large databases. [Citation Graph (0, 0)][DBLP]
    Data Knowl. Eng., 2003, v:46, n:1, pp:97-121 [Journal]
  25. Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet
    Extraction de motifs séquentiels. Problèmes et méthodes. [Citation Graph (0, 0)][DBLP]
    Ingénierie des Systèmes d'Information, 2004, v:9, n:3-4, pp:183-210 [Journal]
  26. Florent Masseglia, Doru Tanasa, Brigitte Trousse
    Diviser pour découvrir. Une méthode d'analyse du comportement de tous les utilisateurs d'un site web. [Citation Graph (0, 0)][DBLP]
    Ingénierie des Systèmes d'Information, 2004, v:9, n:1, pp:61-83 [Journal]
  27. Alice Marascu, Florent Masseglia
    Mining sequential patterns from data streams: a centroid approach. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 2006, v:27, n:3, pp:291-307 [Journal]
  28. Florent Masseglia, Maguelonne Teisseire, Pascal Poncelet
    HDM: A Client/Server/Engine Architecture for Real-Time Web Usage Mining. [Citation Graph (0, 0)][DBLP]
    Knowl. Inf. Syst., 2003, v:5, n:4, pp:439-465 [Journal]
  29. Fatma Bouali, Latifur Khan, Florent Masseglia
    The 6th international workshop on Multimedia Data Mining (MDM/KDD2005). [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2005, v:7, n:2, pp:148-150 [Journal]
  30. Zhongfei Zhang, Florent Masseglia, Ramesh Jain, Alberto Del Bimbo
    KDD/MDM 2006: The 7th KDD Multimedia Data Mining workshop report. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2006, v:8, n:2, pp:92-95 [Journal]

  31. SAX: a privacy preserving general pupose methodapplied to detection of intrusions. [Citation Graph (, )][DBLP]


  32. Discovering Highly Informative Feature Sets from Data Streams. [Citation Graph (, )][DBLP]


  33. Mining Common Outliers for Intrusion Detection. [Citation Graph (, )][DBLP]


  34. Intrusion Detections in Collaborative Organizations by Preserving Privacy. [Citation Graph (, )][DBLP]


  35. Extraction d’itemsets compacts. [Citation Graph (, )][DBLP]


  36. Collaborative Outlier Mining for Intrusion Detection. [Citation Graph (, )][DBLP]


  37. Détection d'enregistrements atypiques dans un flot de données: une approche multi-résolution. [Citation Graph (, )][DBLP]


  38. Détection d'intrusions dans un environnement collaboratif sécurisé. [Citation Graph (, )][DBLP]


  39. Online and adaptive anomaly Detection: detecting intrusions in unlabelled audit data streams. [Citation Graph (, )][DBLP]


  40. REGLO : une nouvelle stratégie pour résumer un flux de séries temporelles. [Citation Graph (, )][DBLP]


  41. Extraction d'itemsets distinctifs dans les flux de données. [Citation Graph (, )][DBLP]


  42. Analysing Satellite Image Time Series by Means of Pattern Mining. [Citation Graph (, )][DBLP]


  43. Des séquences aux tendances. [Citation Graph (, )][DBLP]


  44. A Multi-resolution Approach for Atypical Behaviour Mining. [Citation Graph (, )][DBLP]


  45. Data Mining for Intrusion Detection: From Outliers to True Intrusions. [Citation Graph (, )][DBLP]


  46. Parameterless outlier detection in data streams. [Citation Graph (, )][DBLP]


  47. A fast approximation strategy for summarizing a set of streaming time series. [Citation Graph (, )][DBLP]


  48. Time Aware Mining of Itemsets. [Citation Graph (, )][DBLP]


  49. A general framework for adaptive and online detection of web attacks. [Citation Graph (, )][DBLP]


  50. Web usage mining: extracting unexpected periods from web logs. [Citation Graph (, )][DBLP]


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