Quatrièmes post-actes

Fabrice Guillet, Bruno Pinaud, Gilles Venturini and Djamel Abdelkader Zighed (eds),
« Advances In Knowledge Discovery and Management, Volume 4 »,
Series: Studies in Computational Intelligence,
Vol. 527, 2014, Springer.
ISBN: 978-3-642-25837-4, DOI: 10.1007/978-3-319-02999-3.

About this book

This book is a collection of representative and novel works done in Data Mining, Knowledge Discovery, Clustering and Classification that were originally presented in French at the EGC’2012 Conference held in Bordeaux, France, on January 2012. This conference was the 12th edition of this event, which takes place each year and which is now successful and well-known in the French-speaking community. This community was structured in 2003 by the foundation of the French-speaking EGC societe (EGC in French stands for “Extraction et Gestion des Connaissances” and means “Knowledge Discovery and Management”, or KDM).

Structure of the Book

This book is intended to be read by all researchers interested in these fields, including PhD or MSc students, and researchers from public or private laboratories. It concerns both theoretical and practical aspects of KDM. The book is structured in two parts called “Knowledge Discovery and Data Mining” and “Classification and Feature Extraction or Selection”. The first part (6 chapters) deals with data clustering and data mining. The three remaining chapters of the second part are related to classification and feature extraction or feature selection.

Keywords:

Knowledge Discovery, Knowledge Management, Data Mining, Knowledge Engineering, Applications

Table des matières

Part I — Knowledge Discovery and Data Mining

  • François Queyroi:
    Optimizing a Hierarchical Community Structure of a Complex Network. 3-14
  • Marc Boullé, Romain Guigourès, Fabrice Rossi:
    Nonparametric Hierarchical Clustering of Functional Data. 15-35
  • Francisco de A.T. de Carvalho, Yves Lechevallier, Thierry Despeyroux, Filipe M. de Melo:
    Multi-view Clustering on Relational Data. 37-51
  • Asma Ben Zakour, Sofian Maabout, Mohamed Mosbah, Marc Sistiaga:
    Relaxing Time Granularity for Mining Frequent Sequences. 53-76
  • Rim Faiz, Maha Amami, Aymen Elkhlifi:
    Semantic Event Extraction from Biological Texts Using a Kernel-Based Method. 77-94
  • Dhafer Lahbib, Marc Boullé, Dominique Laurent:
    Supervised Pre-processing of Numerical Variables for Multi-Relational Data Mining. 95-109

Part II — Classification and Feature Extraction or Selection

  • Hassan Chouaib, Florence Cloppet, Nicole Vincent:
    Combination of Single Feature Classifiers for Fast Feature Selection. 113-131
  • Laurent Vézard, Pierrick Legrand, Marie Chavent, Frédérique Faïta-Aïnseba:
    Classification of EEG Signals by an Evolutionary Algorithm. 133-153
  • Thanh-Nghi Doan, François Poulet:
    Large Scale Image Classification: Fast Feature Extraction, Multi-codebook Approach and Multi-core SVM Training. 155-172

Actes Ateliers EGC 2014

Chantal Reynaud, Arnaud Martin, René Quiniou

Site de la conférence EGC 2014

EGC 2013 (Toulouse)

En 2013, deux prix ont été décernés :

  • prix EGC-académique :
    Claude Pasquier, Jérémy Sanhes, Frédéric Flouvat et Nazha Selmaoui-Folcher.
    Extraction de motifs fréquents dans des arbres attribués.
    PPME Nouvelle Calédonnie, IBV Nice
    Revue des Nouvelles Technologies de l’Information E-24, pages 193-204, 2013.
  • prix EGC-application :
    Bourquard Thomas, Damien de Vienne et Jérôme Azé.
    Identification de complexes protéine-protéine par combinaison de classifieurs
    BIOS Group INRA Nouzilly, CFR Barcelone, LRI Orsay

    Revue des Nouvelles Technologies de l’Information E-24, pages 419-430, 2013.

Site EGC 2013

Troisièmes post-actes

Fabrice Guillet, Bruno Pinaud, Gilles Venturini and Djamel Abdelkader Zighed (eds),
« Advances In Knowledge Discovery and Management, Volume 3 »,
Series: Studies in Computational Intelligence,
Vol. 471, 2013, Springer.
ISBN: 978-3-642-25837-4, DOI: 10.1007/978-3-642-35855-5.

About this book

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’2011 Conference held in Brest, France, on January 2011. These 10 best papers have been selected from the 34 papers accepted in long format at the conference. These 34 long papers were themselves the result of a peer and blind review process among the 131 papers initially submitted to the conference in 2011 (acceptance rate of 26% for long papers). This conference was the 11th edition of this event, which takes place each year and which is now successful and well-known in the French-speaking community. This community was structured in 2003 by the
foundation of the International French-speaking EGC society (EGC in French stands for “Extraction et Gestion des Connaissances” and means “Knowledge Discovery and Management”, or KDM). This society organizes every year its main conference (about 200 attendees) but also workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry or public organizations. For more details about the EGC society, please consult https://www.egc.asso.fr.

Structure of the Book

This book is a collection of representative and novel works done in Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and Semantic Web. It is intended to be read by all researchers interested in these fields, including PhD or MSc students, and researchers from public or private laboratories. It concerns both theoretical and practical aspects of KDM.

This book has been structured in two parts. The first part, entitled “Data
Mining, classification and queries”, deals with rule and pattern mining, with topological approaches and with OLAP. Three chapters study rule and pattern mining and concern binary data sets, sequences, and association rules. Chapters related to topological approaches study different distance measures and a new method that learns a hierarchical topological map. Finally, one chapter deals with OLAP and studies the mining of queries logs.
The second part of the book, entitled “Ontology and Semantic”, is more related to knowledge-based and user-centered approaches in KDM. One chapter deals with the enrichment of folksonomies and the three other chapters deal with ontologies.

Written for

Engineers, researchers, and graduate students in computer science

Keywords

Knowledge Discovery, Knowledge Management, Data Mining, Knowledge Engineering, Applications

Table des matières

Part I — Data Mining, Classification and Queries

  • Dominique Gay, Marc Boullé:
    A Bayesian Criterion for Evaluating the Robustness of Classification
    Rules in Binary Data Sets. 3-22
  • Julien Rabatel, Sandra Bringay, Pascal Poncelet:
    Mining Sequential Patterns: A Context-Aware Approach. 23-42
  • Djamel Abdelkader Zighed, Rafik Abdesselam, Ahmed Bounekkar:
    Comparison of Proximity Measures: A Topological Approach. 43-58
  • Israël César Lerman, Sylvie Guillaume:
    Comparing Two Discriminant Probabilistic Interestingness Measures for Association Rules. 59-84
  • Hanane Azzag, Mustapha Lebbah:
    A New Way for Hierarchical and Topological Clustering. 85-98
  • Julien Aligon, Patrick Marcel, Elsa Negre:
    Summarizing and Querying Logs of OLAP Queries. 99-124

Part II — Ontology and Semantic

  • Freddy Limpens, Fabien Gandon, Michel Buffa:
    A Complete Life-Cycle for the Semantic Enrichment of Folksonomies. 127-150
  • Ammar Mechouche, Nathalie Abadie, Emeric Prouteau, Sébastien Mustière:
    Ontology-Based Formal Specifications for User-Friendly Geospatial Data Discovery. 151-176
  • Toader Gherasim, Mounira Harzallah, Giuseppe Berio, Pascale Kuntz:
    Methods and Tools for Automatic Construction of Ontologies from Textual Resources: A Framework for Comparison and Its Application. 177-201
  • Lionel Chauvin, David Genest, Aymeric Le Dorze, Stéphane Loiseau:
    User Centered Cognitive Maps. 203-220