Djamel A. Zighed – författare

This volume contains papers selected for presentation at PKDD'2000, the Fourth European Conference on Principles and Practice of Knowledge Discovery in - tabases. The rst meeting was held in Trondheim, Norway, in June 1997, the second in Nantes, France, in September 1998, and the third in Prague, Czech Republic, in September 1999. PKDD 2000 was organized in Lyon, France, on 13{16 September 2000. The conference was hosted by the Equipe de Recherche en Ing enierie des Conna- sances at the Universit e Lumi ere Lyon 2. We wish to express our thanks to the sponsors of the Conference, to the University Claude Bernard Lyon 1, the INSA of Lyon, the Conseil g en eral of the R^one, the R egion Rh^one Alpes, SPSS France, AFIA, and the University of Lyon 2, for their generous support. Knowledge discovery in databases (KDD), also known as data mining, p- vides tools for turning large databases into knowledge that can be used in pr- tice.KDD has been able to grow very rapidly since its emergence a decade ago by drawing its techniques and data mining experiences from a combination of many existing research areas: databases, statistics, mathematical logic, machine learning, automated scienti c discovery, inductive logic programming, arti cial intelligence, visualization, decision science, knowledge management, and high performance computing. The strength of KDD came initially from the value - ded by the creative combination of techniques from the contributing areas.

This volume contains the papers selected for presentation at the 13th International Symposium on Methodologies for Intelligent Systems ISMIS 2002, held in Lyon, France, 27-29 June, 2002. The symposium was organized by the UniversitO Claude Bernard Lyon 1, the UniversitO Lumiere Lyon 2, l'Institut National des Sciences AppliquOes de Lyon, and hosted by the UniversitO Claude Bernard Lyon 1. The ISMIS conference series was started in 1986 in Knoxville, Tennessee. Since then it has been held in Charlotte (North Carolina), Knoxville (Tennessee), Turin (Italy), Trondheim (Norway), Warsaw (Poland), and Zakopane (Poland). The program committee selected the following major areas for ISMIS 2002: Intelligent Multimedia, Intelligent Information Retrieval, Intelligent Information Systems, Knowledge Representation and Integration, Learning and Knowledge Discovery, Logic for Artificial Intelligence, Methodologies (modeling, design, validation, performance evaluation), and Soft Computing. The contributed papers were selected from approximately 160 full draft papers by the following program committee: L. Carlucci Aiello, N. Belkhiter, P. Berka, E. Bertino, P. Bosc, H. Briand, J. Calmet, S.Carberry, L. Carbonara, B. Catania, T. Catarci, N.J. Cercone, J. Chen, W. Chu, L. De Raedt, J. Debenham, R. Demolombe, B.C. Desai, E. El-Kwae, T. Elomaa, P. Emmerman, F. Esposito, J. Fan, P.A. Flach, P. Gallinari, A. Giordana, M.-S. Hacid, M. Hadzikadic, H.J. Hamilton, D. Hislop, C.A. Johnson, W. Kloesgen, Y. Kodratoff, L. Lakhal, T.Y. Lin, D. Malerba, D. Maluf, S. Matwin, R. Meersman, R.S. Michalski, S. Miguet, M. Mukaidono, N. Nicoloyannis, S. Ohsuga, L.

This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.

The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g.

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.

The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g.