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Perspectives 6FP - Expression of Interest
KDNet 2006 - A Network of Excellence in Data Mining and Knowledge Discovery
Abstract from 1.06.2002 prepared by the KDNet Consortium in response to Call EOI.FP6.2000
Knowledge Discovery or Data Mining is the partially automated process of extracting patterns from usually large databases. It is among the most important methodologies for creating the ambient intelligence landscape envisioned in the eEurope initiative.
The aim of this proposal is to establish Europe as a world-leading force in this area. This will be achieved by close integration of European research activities. The overall research goal is the integration of Knowledge Discovery into knowledge systems and making those systems and services more intelligent. This requires to develop new methods for mining complex data such as text, multimedia and spatial data, to integrate it with knowledge management and decision support systems as well as web based services.
A detailed project proposal has been coordinated and prepared by Fraunhofer AIS (
Dr. Michael May
, Ina Lauth) for the 24th of April 2003.
Consortium Structure (from 01.06.2002)
Management Board:
The proposal has been jointly put forward by the KDNet consortium. The current management board was responsible for organizing the proposal and for preparing the new network. The management board still has open slots for partners who want to take a most active role in the new network. This enlarged management board will form the core group of the network.
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Fraunhofer AIS
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Michael May, Ina Lauth
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Germany
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DM, Statistics, GIS
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Univ. Del Piemonte Orientale
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Lorenza Saitta
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Italy
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DM, ML
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Helsinki Univ. of Technology
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H. Mannila, J. Hollmen
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Finland
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DM, Database Theory
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IJS, Ljubljana
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Dunja Mladenic
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Slovenia
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DM, ML
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Univ. Amsterdam
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Maarten van Someren
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The Netherlands
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ML
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Univ. Magdeburg/Bonn
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Stefan Wrobel
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Germany
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DM
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Univ. Utrecht
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Arno Siebes
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The Netherlands
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DM, Database Theory
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Univ. Dortmund
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Katharina Morik
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Germany
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DM, ML
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DaimlerChrysler
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R. Nakhaeizadeh,
R. Skuppin
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Germany
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Automotive / Transport
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Univ. Bari
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Donato Malerba
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Italy
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DM, ML
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DM = Data Mining, KM Knowledge Managament, ML = Machine Learning (status 1.06.2002)
KDNet II Members:
The consortium currently includes groups from Machine Learning, Statistics, Database Theory, Bioinformatics, Biology, Economics, Geography, Statistical Offices, Global Companies and SME'S from all over Europe. For a proposal, this group will develop more differentiated structures around their specific areas of expertise and interest. Further partners, especially those with complementary expertise will be involved. It is expected that total number of participants in the network will exceed 250 researchers.
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Austrian Research Institute for Artificial Intelligence
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Gerhard Widmer
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Austria
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DM
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Czech Technical University, Prague
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Lenka Lhotska
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Czech republic
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DM, ML
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Department of Computing City, University London
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Eduardo Alonso
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UK
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DM
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Dept. of E-Business, Handelshochschule Leipzig
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Myra Spiliopoulou
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Germany
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DM, KM
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Faculty of Informatics Masaryk University
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Lubos Popelinsky
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Czech Republic
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DM, ML
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FZI Karlsruhe
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Alexander Maedche
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Germany
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KM, Semantic Web
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Handtake GmbH, Köln
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Gerhard Oels
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Germany
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KM
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Infratest Burke, München
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Thomas Liehr
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Germany
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Marketing Research
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INSA de Lyon
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Jean-Francois Boulicaut
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France
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DM
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Inst. d' Investigació en Intelligčncia Artificial CSIC
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Ramon Mantaras
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Spain
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DM, ML
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Institut für Mathematik der Univ. Augsburg
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Antony Unwin
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Germany
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Statistics, Visualization
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International Knowledge Discovery Institute Ltd.
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Joachim Diederich
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Australia
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DM
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JRC Applied Statistics Group, Ispra
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Andrea Saltelli
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Italy
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Statistics
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KTH, Stockholm
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Henrik Boström
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Sweden
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DM, ML
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KUL, Leuven
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Hendrik Blockeel
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Belgium
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DM, ML
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ML group of LIACC, University of Porto
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Joao Gama
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Portugal
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DM
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Perot Systems
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Roy Wagemans
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The Netherlands
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DM
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PharmaDM, Leuven
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Luc Dehaspe
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Belgium
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DM
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Pisa KDD-Lab
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Fosca Gianotti
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Italy
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DM
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Polish Academy of Sciences, Warsaw
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Piotr Dembinski
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Poland
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DM
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Prague University of Economics
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Petr Berka
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Czech republic
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DM, Economics
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Prudential Systems, Chemnitz
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Andreas Ittner
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Germany
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DM
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Royal Holloway, Univ. London
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John Hancock
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UK
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Bioinformatics
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Statistical Bureau of Latvia, Riga
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Karlis Zeila
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Latvia
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Statistical Offices
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Tiaram B.V., Weert
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Peter Ramaekers
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The Netherlands
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KM
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Univ .Karlsruhe, AFIB
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Gerd Stumme
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Germany
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Semantic Web
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Univ. Aberdeen
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D. Sleeman, P. Edwards
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UK
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ML
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Univ. Amsterdam, Zoological Museum
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Wouter Los
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The Netherlands
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Biology
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Univ. Bristol
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Peter. Flach
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UK
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DM, ML
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Univ. Chemnitz
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W. Dilger
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Germany
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DM, ML
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Univ. de Girona, eXiT
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Joaquim Melendez
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Spain
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DM
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Univ. Paris-Sud, LRI
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Celine Rouveirol
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France
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DM, ML
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Univ. Rotterdam
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J. C. Bioch
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The Netherlands
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DM, Economics
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Univ. Ulster
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Ray Hickey
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UK
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DM, ML, Statistics
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University of Helsinki
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Hannu Toivonen
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Finland
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DM
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Wageningen UR Centre for Geo-Information
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Monica Wachowicz
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The Netherlands
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Geoinformatics, DM
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(status 1.06.2002)
The following institutions support the new network without yet (1.06.2002) being members of KDNet:
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Aristotle University, Data Engineering Lab, Thessaloniki
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Yannis Manolopoulos
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Grece
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DM, Databases
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KEGOM, Bayreuth
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Wolfgang Grond
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Germany
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E-Business
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ELCA Informatique SA, Lausanne
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Christophe Giraud
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Switzerland
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DM, Databases
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Facultad de Informática Universidad Politecnica de Madrid
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Ernestina Menasalvas
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Spain
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Web Mining
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INRA (Institut National de la Recherche Agronomique)
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Claire NĂ©delec
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France
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DM
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Isoft
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HĂ©rve Perdrix
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France
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DM
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KCL , Espoo
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Risto Ristala
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Finland
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Dynamic Processes
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Poznan Univ. of Tech.
Intelligent Dec. Support Systems Lab
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Krzysztof Krawiec
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Poland
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DM
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Rudjer Boskovic Institute, Zagreb
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Dragan Gamberger
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Croatia
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DM, ML
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Software Achkar GmbH, Sankt Augustin
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Najib Achkar
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Germany
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KM, IT
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University of Crete, Information Systems Laboratory
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Panos Constantopoulos
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Greece
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DM
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University of Ljubljana, Artificial intelligence laboratory
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Dorian Suc
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Slovenia
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DM
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Univ. of Paris VI, Jeune Equipe CNRS, “Découverte”
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Jean-Daniel Zucker
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France
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DM, ML
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Univ.
Torino, Dept. of Informatica
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R. Meo, M. Botta
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Italy
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DM, ML
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Univ. Portsmouth
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Max Bramer
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UK
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DM, AI
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(status 1.06.2002)
Funding scheme
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Institution Member
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Overall coordination, network meetings
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Network workplan
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Dissemination
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Online Information Services, Newsletters, promotion
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Network workplan
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Integration activities
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Running the Virtual KDD lab, Organizing cluster meetings, tutorials, workshops
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Network workplan
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Research grants
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to carry out activities closely related to the networks research needs, normally involves exchange of personnel
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Proposal (continuous submission), peer review
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Integration projects
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Two existing (e.g. national) projects identify thematic overlap and launch joint work related to the original proposal, exploiting synergies
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Proposal (continuous submission), peer review
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Joint research projects
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Larger scale projects involving several groups for implementing the network’s research objectives
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Call for proposals, peer review
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Links
MLNet
- Machine Learning Network Online Information System
Knowledge Aquisition
- Knowledge Aquisition Workshops and Archives
KDnuggets
- KDnugetts Directory Data Mining and Knowledge Discovery resources
ILPNet2
- Network of Excellence in Inductive Logic Programming ILPnet2
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