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Advances in Knowledge Discovery and Management

Volume 8

  • Bruno Pinaud
  • Fabrice Guillet
  • Fabien Gandon
  • Christine Largeron
Book

Part of the Studies in Computational Intelligence book series (SCI, volume 834)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Clustering

    1. Front Matter
      Pages 1-1
    2. Aichetou Bouchareb, Marc Boullé, Fabrice Clérot, Fabrice Rossi
      Pages 3-22
    3. Aichetou Bouchareb, Marc Boullé, Fabrice Clérot, Fabrice Rossi
      Pages 23-41
  3. Textual Data

    1. Front Matter
      Pages 43-43
    2. Julien Hay, Tim Van de Cruys, Philippe Muller, Bich-Liên Doan, Fabrice Popineau, Ouassim Ait-Elhara
      Pages 45-60
    3. Gildas Tagny Ngompé, Sébastien Harispe, Guillaume Zambrano, Jacky Montmain, Stéphane Mussard
      Pages 61-86
  4. Spatial and Temporal Dimension

    1. Front Matter
      Pages 87-87
    2. Yann Dauxais, David Gross-Amblard, Thomas Guyet, André Happe
      Pages 89-118
    3. Anne Toulet, Emmanuel Roux, Anne-Élisabeth Laques, Éric Delaître, Laurent Demagistri, Isabelle Mougenot
      Pages 119-136
  5. Human and Social Dimension

    1. Front Matter
      Pages 137-137
    2. Jean-Christophe Dubois, Laetitia Gros, Mouloud Kharoune, Yolande Le Gall, Arnaud Martin, Zoltan Miklos et al.
      Pages 139-157
    3. Benjamin Costé, Cyril Ray, Gouenou Coatrieux
      Pages 159-181
  6. Back Matter
    Pages 183-183

About this book

Introduction

This book highlights novel research in Knowledge Discovery and Management (KDM), gathering the extended, peer-reviewed versions of outstanding papers presented at the annual conferences EGC’2017 & EGC’2018. The EGC conference cycle was founded by the International French-speaking EGC society (“Extraction et Gestion des Connaissances”) in 2003, and has since become a respected fixture among the French-speaking community. In addition to the annual conference, the society organizes various other events in order to promote exchanges between researchers and companies concerned with KDM and its applications to business, administration, industry and public organizations.

Addressing novel research in data science, semantic Web, clustering, and classification, the content presented here will chiefly benefit researchers interested in these fields, including Ph.D./M.Sc. students, at public and private laboratories alike.

Keywords

Data Science Semantic Web Clustering and Classification Computational Intelligence Knowledge Management

Editors and affiliations

  • Bruno Pinaud
    • 1
  • Fabrice Guillet
    • 2
  • Fabien Gandon
    • 3
  • Christine Largeron
    • 4
  1. 1.University of BordeauxBordeauxFrance
  2. 2.Polytechnic School of the University of NantesUniversity of NantesNantesFrance
  3. 3.University of Côte d'AzurInriaSophia AntipolisFrance
  4. 4.CNRS, Hubert Curien LaboratoryUniversity of Lyon, Université Jean Monnet, Saint-EtienneSaint-ÉtienneFrance

Bibliographic information