Association EGC

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

Fabrice Guillet, Gilbert Ritschard and Djamel Abdelkader Zighed (eds),
« Advances In Knowledge Discovery and Management, Volume 2 »,
Series: Studies in Computational Intelligence,
Volume 398, 2012, Springer.
ISBN: 978-3-642-25837-4, DOI: 10.1007/978-3-642-25838-1.

L’ouvrage est accessible en édition électronique sur Springer Link.

Cliquez ici pour télécharger la préface et la table des matières »

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About this book

During the last decade, Knowledge Discovery and Management (KDM or, in French, EGC for Extraction et Gestion des connaissances) has been an intensive and fruitful research topic in the French-speaking scientific community. In 2003, this enthusiasm for KDM led to the foundation of a specific French-speaking association, called EGC, dedicated to supporting and promoting this topic. More precisely, KDM is concerned with the interface between knowledge and data such as, among other things, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and Semantic Web. 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 2010 Conference held in Tunis, Tunisia in January 2010.
The volume is organized in three parts. Part I includes four chapters concerned with various aspects of Data Cube and Ontology-based representations. Part II is composed of four chapters concerned with Efficient Pattern Mining issues, while in Part III the last four chapters address Data Preprocessing and Information Retrieval.

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 Cube and Ontology-based representations

• Rosine Cicchetti, Lotfi Lakhal, and Sébastien Nedjar:
  Constrained Closed and Quotient Cubes. 3-26
• Hanen Brahmi, Tarek Hamrouni, Riadh Ben Messaoud, and Sadok Ben Yahia:
  A New Concise and Exact Representation of Data Cubes. 27-48
• Michel Buffa and Catherine Faron-Zucker:
  Ontology-Based Access Rights Management. 49-62
• Souhir Gahbiche, Nathalie Pernelle, and Fatiha Saïs:
  Explaining Reference Reconciliation Decisions: a Coloured Petri Nets based approach. 63-84

Part II — Efficient Pattern Mining

• Mehdi Khiari, Patrice Boizumault, and Bruno Crémilleux:
  Combining Constraint Programming and Constraint-based Mining for Pattern Discovery. 85-104
• Marc Boullé:
  Simultaneous Partitioning of Input and Class Variables for Supervised Classification Problems with Many Classes. 105-120
• Lionel Martin, Matthieu Exbrayat, Guillaume Cleuziou, and Frédéric Moal:
  Interactive and progressive constraint definition for dimensionality reduction and visualization. 121-138
• Anne Laurent, Benjamin Négrevergne, Nicolas Sicard, and Alexandre Termier:
  Efficient parallel mining of gradual patterns on multicore processors. 139-156

Part III — Data Preprocessing and Information Retrieval

• Mickael Coustaty, Vincent Courboulay, and Jean-Marc Ogier:
  Analyzing Old Documents Using a Complex Approach: application to lettrines indexing. 157-174
• Marc Joliveau:
  Identifying relevant features of images from their 2-D topology. 175-192
• Radja Messai and Michel Simonet and Nathalie Bricon-Souf and Mireille Mousseau:
  Analyzing Health Consumer Terminology for Query Reformulation Tasks. 193-214
• Patrick Bosc, Allel Hadjali, Olivier Pivert, and Grégory Smits:
  An approach based on predicate correlation to the reduction of plethoric answer sets. 215-236