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Research interests

My thesis is supervised by professor Richard Nock and is monitored by Mr Jean-Émile Symphor (assistant professor). This thesis is supported by the Regional Council of Martinique and is conducted within two research projects : ISIS and MIDAS.

My researches focusses upon the knowledge discovery in data streams, particularly the extraction of temporal Patterns. I work in Martinique, at the University of the French West Indies and Guiana (french spelled "Université des Antilles et de la Guyane" or UAG), and I am affiliated to CEREGMIA. I work on Data Mining problems such as :

Other link : List of publications on DBLP

Papers

  1. Résumé généraliste de flux de données.
    Collectif d'auteurs issus du projet MIDAS. - EGC'2010 - pdf - (ar: 23%)
  2. SALINES : un automate au service de l'extraction de motifs sequentiels multidimensionnels
    Yoann Pitarch, Lionel Vinceslas, Anne Laurent, Pascal Poncelet, Jean-Emile Symphor - EGC'2010 - pdf - (ar: 26%)
  3. Spams, un nouvel algorithme incrémental pour l'extraction de motifs séquentiels dans les Data Stream
    Lionel Vinceslas, Jean-Emile Symphor, Alban Mancheron, Pascal Poncelet - EGC'2009 - - (ar: 20%)
  4. Le FIA: un nouvel automate permettant l'extraction efficace d'itemsets fréquents dans les flots de données.
    Jean-Emile Symphor, Alban Mancheron, Lionel Vinceslas, Pascal Poncelet - EGC'2008 - pdf - - (ar: 33%)
  5. FIASCO: un nouvel algorithme d'extraction d'itemsets fréquents dans les flots de données.
    Lionel Vinceslas, Jean-Emile Symphor, Alban Mancheron, Pascal Poncelet - EGC'2008

Book Chapter

  1. SPAMS: a Novel Incremental Approach to Sequential Patterns Mining in Data Streams
    Lionel Vinceslas, Jean-Emile Symphor, Alban Mancheron, Pascal Poncelet - Advances in Knowledge Discovery and Management, Studies in Computational Intelligence, 2010, Volume 292/2010, pages 201-216

Activities

Reports

Legend : = Download PDF; = Selected for Best Paper Award; = Best Paper Award; ar= Acceptance Rate.