Bruno Pinaud – författare

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.

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 emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges.

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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".

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).

This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks.Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.

This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of “Knowledge Discovery and Management” (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories.The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC’2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.

This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks.Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.

This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of “Knowledge Discovery and Management” (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories.The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC’2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.

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.