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Pascal Poncelet: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Pascal Poncelet, Maguelonne Teisseire, Rosine Cicchetti, Lotfi Lakhal
    Towards a Formal Approach for Object Database Design. [Citation Graph (5, 25)][DBLP]
    VLDB, 1993, pp:278-289 [Conf]
  2. Maguelonne Teisseire, Pascal Poncelet, Rosine Cicchetti
    Dynamic Modelling with Events [Citation Graph (2, 0)][DBLP]
    CAiSE, 1994, pp:186-199 [Conf]
  3. Maguelonne Teisseire, Pascal Poncelet, Rosine Cicchetti
    Towards Event-Driven Modelling for Database Design. [Citation Graph (2, 18)][DBLP]
    VLDB, 1994, pp:285-296 [Conf]
  4. Pascal Poncelet, Lotfi Lakhal
    Consistent Structural Updates for Object Database Design [Citation Graph (1, 0)][DBLP]
    CAiSE, 1993, pp:1-21 [Conf]
  5. Rachid Arezki, Pascal Poncelet, Gérard Dray, David William Pearson
    Web Information Retrieval Based on User Profile. [Citation Graph (0, 0)][DBLP]
    AH, 2004, pp:275-278 [Conf]
  6. Rachid Arezki, Pascal Poncelet, Gérard Dray, David William Pearson
    Information Retrieval Model Based on User Profile. [Citation Graph (0, 0)][DBLP]
    AIMSA, 2004, pp:490-499 [Conf]
  7. 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]
  8. 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]
  9. Rosine Cicchetti, Pascal Poncelet, Maguelonne Teisseire
    Une Aide à la conception et au Contrôle de Règles actives. [Citation Graph (0, 0)][DBLP]
    BDA, 1996, pp:19-0 [Conf]
  10. Vishal Kapoor, Pascal Poncelet, François Trousset, Maguelonne Teisseire
    Privacy Preserving Sequential Pattern Mining in Distributed Databases. [Citation Graph (0, 0)][DBLP]
    BDA, 2006, pp:- [Conf]
  11. Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
    Incremental Mining of Sequential Patterns in Large Databases. [Citation Graph (0, 0)][DBLP]
    BDA, 2000, pp:- [Conf]
  12. 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]
  13. 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]
  14. Pascal Poncelet, Maguelonne Teisseire, Lotfi Lakhal
    IFO2, modèle et principe pour la conception de bases de données avancées. [Citation Graph (0, 0)][DBLP]
    BDA, 1992, pp:320-0 [Conf]
  15. Chedy Raïssi, Pascal Poncelet, Maguelonne Teisseire
    Need For Speed : Mining Sequential Patterns in Data Streams. [Citation Graph (0, 0)][DBLP]
    BDA, 2005, pp:- [Conf]
  16. Zohra Bellahsene, Pascal Poncelet, Maguelonne Teisseire
    Views for Information System Design without Reorganization. [Citation Graph (0, 0)][DBLP]
    CAiSE, 1996, pp:496-513 [Conf]
  17. Fabienne Cathala, Pascal Poncelet
    Preserving Behaviour: Why and How. [Citation Graph (0, 0)][DBLP]
    CAiSE, 1997, pp:333-346 [Conf]
  18. Pierre-Alain Laur, Richard Nock, Jean-Emile Symphor, Pascal Poncelet
    On the estimation of frequent itemsets for data streams: theory and experiments. [Citation Graph (0, 0)][DBLP]
    CIKM, 2005, pp:327-328 [Conf]
  19. Vishal Kapoor, Pascal Poncelet, François Trousset, Maguelonne Teisseire
    Privacy preserving sequential pattern mining in distributed databases. [Citation Graph (0, 0)][DBLP]
    CIKM, 2006, pp:758-767 [Conf]
  20. Rachid Arezki, Pascal Poncelet, Gérard Dray, David William Pearson
    Représentation Dynamique de Documents pour une Recherche Documentaire Intelligente. [Citation Graph (0, 0)][DBLP]
    CORIA, 2005, pp:219-234 [Conf]
  21. Maguelonne Teisseire, Pascal Poncelet, Rosine Cicchetti
    IFO2: a Uniform Approach for Information System Modelling. [Citation Graph (0, 0)][DBLP]
    DAISD, 1994, pp:33-53 [Conf]
  22. Pierre-Alain Laur, Maguelonne Teisseire, Pascal Poncelet
    AUSMS: An Environment for Frequent Sub-structures Extraction in a Semi-structured Object Collection. [Citation Graph (0, 0)][DBLP]
    DEXA, 2003, pp:38-45 [Conf]
  23. Florent Masseglia, Pascal Poncelet, Rosine Cicchetti
    WebTool: An Integrated Framework for Data Mining. [Citation Graph (0, 0)][DBLP]
    DEXA, 1999, pp:892-901 [Conf]
  24. Rachid Arezki, Abdenour Mokrane, Gérard Dray, Pascal Poncelet, David William Pearson
    Modélisation dynamique et temporelle de l'utilisateur pour un filtrage personnalisé de documents textuels. [Citation Graph (0, 0)][DBLP]
    EGC, 2004, pp:479-484 [Conf]
  25. Philippe Collet, Vincent Derozier, Gérard Dray, François Trousset, Pascal Poncelet, Michel Crampes
    Tendances dans les expressions de gènes : application à l'analyse du transcriptome de Plasmodium Falciparum. [Citation Graph (0, 0)][DBLP]
    EGC, 2005, pp:649-654 [Conf]
  26. Pierre-Alain Laur, Pascal Poncelet
    AUSMS : un environnement pour l'extraction de sous-structures fréquentes dans une collection d'objets semi-structurés. [Citation Graph (0, 0)][DBLP]
    EGC, 2003, pp:449-459 [Conf]
  27. 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]
  28. Federico Del Razo López, Anne Laurent, Pascal Poncelet, Maguelonne Teisseire
    Recherche de sous-structures fréquentes pour l'intégration de schémas XML. [Citation Graph (0, 0)][DBLP]
    EGC, 2006, pp:487-498 [Conf]
  29. 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]
  30. 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]
  31. Chedy Raïssi, Pascal Poncelet
    Vers une nouvelle approche d'extraction des motifs séquentiels non-dérivables. [Citation Graph (0, 0)][DBLP]
    EGC, 2007, pp:307-318 [Conf]
  32. Rachid Arezki, Abdenour Mokrane, Gérard Dray, Pascal Poncelet, David William Pearson
    LUCI: A Personalization Documentary System Based on the Analysis of the History of the User's Actions. [Citation Graph (0, 0)][DBLP]
    FQAS, 2004, pp:487-498 [Conf]
  33. Pierre-Alain Laur, Maguelonne Teisseire, Pascal Poncelet
    Web Usage Mining: Extraction, Maintenance and Behaviour Trends. [Citation Graph (0, 0)][DBLP]
    IICAI, 2003, pp:493-506 [Conf]
  34. Rosine Cicchetti, Pascal Poncelet, Maguelonne Teisseire
    Modélisation et validation comportementales. [Citation Graph (0, 0)][DBLP]
    INFORSID, 1996, pp:407-425 [Conf]
  35. Florent Masseglia, Pascal Poncelet, Rosine Cicchetti
    Webtool: un environnement intégré de data mining. [Citation Graph (0, 0)][DBLP]
    INFORSID, 1999, pp:393-411 [Conf]
  36. Pierre-Alain Laur, Jean-Emile Symphor, Richard Nock, Pascal Poncelet
    Statistical Supports for Frequent Itemsets on Data Streams. [Citation Graph (0, 0)][DBLP]
    MLDM, 2005, pp:395-404 [Conf]
  37. Florent Masseglia, Fabienne Cathala, Pascal Poncelet
    The PSP Approach for Mining Sequential Patterns. [Citation Graph (0, 0)][DBLP]
    PKDD, 1998, pp:176-184 [Conf]
  38. 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]
  39. 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]
  40. 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]
  41. 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]
  42. 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]
  43. 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]
  44. Pierre-Alain Laur, Jean-Emile Symphor, Richard Nock, Pascal Poncelet
    Statistical supports for mining sequential patterns and improving the incremental update process on data streams. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2007, v:11, n:1, pp:29-47 [Journal]
  45. 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]
  46. Pierre-Alain Laur, Maguelonne Teisseire, Pascal Poncelet
    Données semi-structurées. Découverte, maintenance et analyse de tendances. [Citation Graph (0, 0)][DBLP]
    Ingénierie des Systèmes d'Information, 2003, v:8, n:5-6, pp:49-78 [Journal]
  47. Chedy Raïssi, Pascal Poncelet, Maguelonne Teisseire
    Towards a new approach for mining frequent itemsets on data stream. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 2007, v:28, n:1, pp:23-36 [Journal]
  48. 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]
  49. Pierre-Alain Laur, Richard Nock, Jean-Emile Symphor, Pascal Poncelet
    Mining evolving data streams for frequent patterns. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2007, v:40, n:2, pp:492-503 [Journal]
  50. Federico Del Razo López, Anne Laurent, Pascal Poncelet, Maguelonne Teisseire
    Fuzzy Tree Mining: Go Soft on Your Nodes. [Citation Graph (0, 0)][DBLP]
    IFSA, 2007, pp:145-154 [Conf]

  51. Multidimensional Data Stream Summarization Using Extended Tilted-Time Windows. [Citation Graph (, )][DBLP]


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


  53. A novel approach for privacy mining of generic basic association rules. [Citation Graph (, )][DBLP]


  54. Recherche de passages pertinents dans les fichiers logs par enrichissement de requêtes. [Citation Graph (, )][DBLP]


  55. Is a Voting Approach Accurate for Opinion Mining?. [Citation Graph (, )][DBLP]


  56. Extraction of Opposite Sentiments in Classified Free Format Text Reviews. [Citation Graph (, )][DBLP]


  57. Terminology Extraction from Log Files. [Citation Graph (, )][DBLP]


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


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


  60. SPAMS: A Novel Incremental Approach for Sequential Pattern Mining in Data Streams. [Citation Graph (, )][DBLP]


  61. Le FIA: un nouvel automate permettant l’extraction efficace d’itemsets fréquents dans les flots de données. [Citation Graph (, )][DBLP]


  62. Découverte de motifs séquentiels et règles inattendues. [Citation Graph (, )][DBLP]


  63. FIASCO : un nouvel algorithme d’extraction d’itemsets fréquents dans les flots de données. [Citation Graph (, )][DBLP]


  64. Échantillonnage pour l’extraction de motifs séquentiels : des basesde données statiques aux flots de données. [Citation Graph (, )][DBLP]


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


  66. Motifs graduels clos. [Citation Graph (, )][DBLP]


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


  68. SPAMS: Une nouvelle approche incrémentale pour l'extraction de motifs séquentiels fréquents dans les data streams. [Citation Graph (, )][DBLP]


  69. Salines : un automate au service de l'extraction de motifs séquentiels multidimensionnels. [Citation Graph (, )][DBLP]


  70. Requêtes Skyline avec prise en compte des préférences utilisateurs pour des données volumineuses. [Citation Graph (, )][DBLP]


  71. Une structure basée sur les hiérarchies pour synthétiser les itemsets fréquents extraits dans des fenêtres temporelles. [Citation Graph (, )][DBLP]


  72. Bien cube, les données textuelles peuvent s'agréger ! [Citation Graph (, )][DBLP]


  73. Aide à la décision pour la maintenance ferroviaire préventive. [Citation Graph (, )][DBLP]


  74. Mining Closed Gradual Patterns. [Citation Graph (, )][DBLP]


  75. Sampling for Sequential Pattern Mining: From Static Databases to Data Streams. [Citation Graph (, )][DBLP]


  76. Mining Unexpected Web Usage Behaviors. [Citation Graph (, )][DBLP]


  77. SO_MAD: SensOr Mining for Anomaly Detection in Railway Data. [Citation Graph (, )][DBLP]


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


  79. Summarizing Multidimensional Data Streams: A Hierarchy-Graph-Based Approach. [Citation Graph (, )][DBLP]


  80. Mining Conjunctive Sequential Patterns. [Citation Graph (, )][DBLP]


  81. Passage Retrieval in Log Files: An Approach Based on Query Enrichment. [Citation Graph (, )][DBLP]


  82. MAD-IDS: Novel Intrusion Detection System Using Mobile Agents and Data Mining Approaches. [Citation Graph (, )][DBLP]


  83. SS-IDS: Statistical Signature Based IDS. [Citation Graph (, )][DBLP]


  84. RSF - A New Tree Mining Approach with an Ecient Data Structure. [Citation Graph (, )][DBLP]


  85. Recognizing unexpected recurrence behaviors with fuzzy measures in sequence databases. [Citation Graph (, )][DBLP]


  86. Web opinion mining: how to extract opinions from blogs? [Citation Graph (, )][DBLP]


  87. A conceptual model for handling personalized hierarchies in multidimensional databases. [Citation Graph (, )][DBLP]


  88. Mining for Relevant Terms from Log Files. [Citation Graph (, )][DBLP]


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


  90. Mining conjunctive sequential patterns. [Citation Graph (, )][DBLP]


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