ECML/PKDD2004 Discovery Challenge

September 20, 2004

Workshop Program

9:00-10:30 Introduction + Atherosclerosis data session 1: mining sequential data

beginAuthorsTitle
9:00Berka, P. (University of Economics, Prague, Czech Republic) Introduction to the Discovery Challenge (presentation)
9:10Tomeckova, M. (EuroMISE Centre, Prague, Czech Republic) The challenge on atherosclerosis data viewed by the experts (presentation)
9:30 Brisson L., Pasquier N., Collard M., Hébert C. (Université de Nice and Université de Caen, France) HASAR: mining sequential association rules for atherosclerosis factor analysis (ps file) (presentation)
9:50Klema J., Novakova L., Karel F., Stepankova O.(Czech Technical University, Czech Republic) Trend analysis in Stulong data (pdf file) (presentation)
10:10Meger N., Leschi C., Lucas N., Rigotti C. (INSA de Lyon and Université d'Orsay, France) Mining episode rules in STULONG dataset (pdf file) (presentation)

10:30-11:00 coffee break

11:00-12:30 Atherosclerosis data session 2: rules and characterization

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11:00Durand N., Cleuziou G., Soulet A. (Université de Caen and Université d'Orléans, France) Discovery of overlapping clusters to detect atherosclerosis risk factors (ps file)
11:20Goncalves E.C., Plastino A. (Universidade Federal Fluminense, Brazil) Mining strong associations and exceptions in the STULONG data set (pdf file) (presentation)
11:40Soulet A., Hébert C. (Université de Caen) Using emerging patterns from clusters to characterize social subgroups of patients affected by atherosclerosis (pdf file)
12:00Salleb A., Turmeaux T., Vrain C., Nortet C. (Université d'Orléans) Mining quantitative association rules in a atherosclerosis dataset (pdf file)
12:15Couturier O., Delalin H., Fu H., Kouamou G. E., Mephu-Nguifo E. (Université de Lens, France) A three-step approach for STULONG database analysis: characterization of patients' groups (pdf file) (presentation)

12:30-14:00 lunch

14:00 - 15:30 Atherosclerosis data session 3, Gene expression data

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14:00Oka M., Koiso T., Meng E., Kato K. (University of Tsukuba, University of Colorado and Japan Science and Technology Corporation, Japan) Extracting features of patients using the Eigen co-occurrence matrix algorithm (pdf file)
14:20Lachiche N., Fuchs S., Gançarski P. and Derivaux S. (Université de Strasbourg, France) Discriminative power of related controls in the STULONG project (pdf file)
14:30 Blatak J. (Masaryk University in Brno, Czech Republic) Mining first-order frequent patterns in the STULONG database (pdf file) (presentation)
14:40Robardet, C. (Universite Claude Bernard Lyon, France) The challenge on gene expression data viewed by the experts (presentation)
15:00 Rioult F. (Université de Caen) Mining strong emerging patterns in wide SAGE data (pdf file) (presentation)
15:20 Gamberoni G., Storari S. (Universita di Ferrara, Italy) Supervised and unsupervised learning techniques for profiling SAGE results (ps file)

15:30-16:00 coffee break

16:00-18:15 Hepatitis data, Panel with experts

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16:00 The challenge on hepatitis data viewed by the experts
16:20Hirano S., Tsumoto S. (School of Medicine, Shimane University, Japan) Identification of inhomogeneous/short sequneces in the chronic hepatitis dataset based on the variance of sampling interval (pdf file)
16:40 Ho, T. B., Kawasaki S., Le S. G., Tran T. N., Takabayashi K., Yokoi H. (School of Knowledge Science, Ishikawa and Chiba University Hospital, Chiba, Japan) Combining temporal abstraction and data mining to sudy hepatitis (pdf file)
17:00 Ohara K., Yoshida T., Geamsakul W., Motoda H., Washio T., Yokoi H., Takabayashi K. (Osaka University, Hokkaido University and Chiba University Hospital, Chiba, Japan) Analysis of hepatitis dataset by decision tree graph-based induction (pdf file)
17:20 Suzuki E., Zhong N., Yokoi H., Takabayashi K. (Yokohama University, Maebashi Institute of Technology, Japan) Spiral mining of chronic hepatitis data (pdf file)
17:40 Riguzzi F. (Universita di Ferrara, Italy) Classification and visualisation on the hepatitis dataset (pdf file)
17:50Panel with experts (presentation)