Djamel Abdelkader Zighed – författare

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 society (EGC in French stands for ``Extraction et Gestion des Connaissances'''' and means ``Knowledge Discovery and Management'''', or KDM).

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.

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''2013 (Toulouse, France, January 2013) and EGC''2014 Conferences (Rennes, France, January 2014). These conferences were respectively the 13th and 14th editions 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 society (EGC in French stands for "Extraction et Gestion des Connaissances" and means "Knowledge Discovery and Management", or KDM).

This book is aiming at 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 "Applications of KDM to real datasets" and "Foundations of KDM".

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.

The recent and novel research contributions collected in this book are extended andreworked versions of a selection of the best papers that were originally presented inFrench at the EGC’2011 Conference held in Brest, France, on January 2011.EGC stands for "Extraction et Gestion des connaissances" in French, and means "Knowledge Discovery and Management" or KDM.KDM is concerned with the works in computer science at the interface between data and knowledge; such as Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and Semantic Web. This book is intended to be read by all researchers interested in these fields, includingPhD or MSc students, and researchers from public or private laboratories. Itconcerns 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 approachesand with OLAP.The second part of the book, entitled “Ontology and Semantic”, is relatedto knowledge-based and user-centered approaches in KDM.