First International Workshop on

Mining Graphs, Trees and Sequences (MGTS-2003)

Workshop Program

Preface


9:00 Opening

9:05 Invited Tutorial

An Introduction to Kernel Methods for Mining Graph Data
Thomas Gaertner
Fraunhofer Institut Autonome Intelligence Systeme and University of Bonn

Mining Tree Structures
10:05
Probabilistic Approach for Reduction of Irrelevant Tree-structured Data
Amaury Habrard, Marc Bernard and Marc Sebban
Universite Jean Monnet de Saint-Etienne

10:30-11:00 Break

Mining Tree Structures (continue)
11:00
Effcient Discovery of Frequent Unordered Trees
Siegfried Nijssen and Joost N. Kok
Leiden Institute of Advanced Computer Science
11:25
Distance-based Clustering of XML Documents
Francesco De Francesca, Gianluca Gordano, Riccardo Ortale and Andrea Tagarelli
University of Calabria

Mining Graph Structures
11:40
Expressivity versus Efficiency of Grapgh Kernels
Jan Ramon and Thomas Gaertner
K.U. Leuven, Fraunhofer Institut Autonome Intelligence Systeme
and University of Bonn
12:05
Learning Logic Programs with Unary Partial Function Graph Background Knowledge
Tamas Horvath, Robert H. Sloan and Gyorgy Turan
University of Bonn, Fraunhofer Institut Autonome Intelligence Systeme,
University of Illinois at Chicago and Hungarian Academy of Sciences

12:30-14:00 Lunch

Mining Graph Structures (continue)
14:00
Constructing a Decision Tree for Graph Structured Data
Warodom Geamsakul, Takashi Matsuda, Tetsuya Yoshida, Hiroshi Motoda and Takashi Washio
Osaka University
14:25
Effective Rule Induction from Molecular Structures Represented by Labeled Graph
Susanne Hoche, Tamas Horvath and Stefan Wrobel
Fraunhofer Institut Autonome Intelligence Systeme and University of Bonn
14:50
Specific Biasis for Mining Frequent Substructures
Akihiro Inokuchi, Takashi Washio and Hiroshi Motoda
IBM Japan and Osaka University
15:15
Graph Mining Approaches for the Discovery of Web Communities
Tsuyoshi Murata
National Institute of Informatics and Japan Science and Technology Corporation

15:30 Closing


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