Advances in Knowledge Discovery and Management

1. Front Matter

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2. Supervised Learning and Information Retrieval

   1. Front Matter

      Pages 1-1

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   2. Discrepancy Analysis of Complex Objects Using Dissimilarities

      • Matthias Studer, Gilbert Ritschard, Alexis Gabadinho, Nicolas S. Müller

      Pages 3-19

   3. A Bayes Evaluation Criterion for Decision Trees

      • Nicolas Voisine, Marc Boullé, Carine Hue

      Pages 21-38

   4. Classifying Very-High-Dimensional Data with Random Forests of Oblique Decision Trees

      • Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich, Nguyen-Khang Pham

      Pages 39-55

   5. Intensive Use of Correspondence Analysis for Large Scale Content-Based Image Retrieval

      • Nguyen-Khang Pham, Annie Morin, Patrick Gros, Quyet-Thang Le

      Pages 57-76

   6. Toward a Better Integration of Spatial Relations in Learning with Graphical Models

      • Emanuel Aldea, Isabelle Bloch

      Pages 77-94

3. Unsupervised Learning

   1. Front Matter

      Pages 95-95

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   2. Multigranular Manipulations for OLAP Querying

      • Gilles Hubert, Olivier Teste

      Pages 97-112

   3. A New Approach for Unsupervised Classification in Image Segmentation

      • Sébastien Lefèvre

      Pages 113-131

   4. Cluster-Dependent Feature Selection through a Weighted Learning Paradigm

      • Nistor Grozavu, Younès Bennani, Mustapha Lebbah

      Pages 133-147

   5. Two Variants of the OKM for Overlapping Clustering

      • Guillaume Cleuziou

      Pages 149-166

   6. A Stable Decomposition Algorithm for Dynamic Social Network Analysis

      • Romain Bourqui, Paolo Simonetto, Fabien Jourdan

      Pages 167-178

4. Security and Data Streaming

   1. Front Matter

      Pages 179-179

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   2. An Hybrid Data Stream Summarizing Approach by Sampling and Clustering

      • Nesrine Gabsi, Fabrice Clérot, Georges Hébrail

      Pages 181-200

   3. SPAMS: A Novel Incremental Approach for Sequential Pattern Mining in Data Streams

      • Lionel Vinceslas, Jean-Emile Symphor, Alban Mancheron, Pascal Poncelet

      Pages 201-216

   4. Mining Common Outliers for Intrusion Detection

      • Goverdhan Singh, Florent Masseglia, Céline Fiot, Alice Marascu, Pascal Poncelet

      Pages 217-234

   5. Intrusion Detections in Collaborative Organizations by Preserving Privacy

      • Nischal Verma, François Trousset, Pascal Poncelet, Florent Masseglia

      Pages 235-247

5. Ontologies and Semantic

   1. Front Matter

      Pages 249-249

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   2. Alignment-Based Partitioning of Large-Scale Ontologies

      • Fayçal Hamdi, Brigitte Safar, Chantal Reynaud, Haïfa Zargayouna

      Pages 251-269

During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.

• Ontologie
• Spam
• data mining
• database
• databases
• image segmentation
• knowledge
• knowledge discovery
• learning
• management
• organization
• semantic web

• Polytechnic School of Nantes University, Nantes, France

  Fabrice Guillet, Henri Briand

• Université de Genève, Genève, Switzerland

  Gilbert Ritschard

• Université Lumi‘́ere Lyon 2, Bron, France

  Djamel Abdelkader Zighed

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