Monday, September 22
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| 09:00
- 17:00 Workshops and Tutorials |
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Tutorial-Workshop
1
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Panorama
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Context-Free Grammar Learning
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Colin de la Higuera, Jose
Oncina, Pieter Adriaans, Menno van Zaanen
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Tutorial-Workshop
2
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Bobara
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Adaptive Text Extraction and Mining
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Fabio Ciravegna, Nicholas
Kushmerick
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Workshop
1
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Libertas
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First European Web Mining Forum
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Bettina Berendt, Andreas
Hotho, Dunja Mladenic, Maarten van Someren, Myra Spiliopoulou, Gerd
Stumme
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Workshop
2
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Sipun
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Multimedia Discovery and Mining
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Dunja Mladenic, Gerhard
Paass
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Workshop
3
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Ragusa |
Data Mining and Text Mining in
Bioinformatics
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Tobias Scheffer, Ulf Leser
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Workshop
4
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Orlando
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Knowledge Discovery in Inductive Databases
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Jean-François
Boulicaut, Saso Dzeroski, Mika Klemettinen, Rosa Meo, Luc De Raedt
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Tuesday, September 23
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top |
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| 09:00
- 15:30 Workshops and Tutorials |
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09:00 -
15:30 Workshop 5
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Ragusa |
Graph, Tree, and Sequence Mining
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Luc De Raedt, Takashi
Washio
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09:00 -
15:30 Workshop 6
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Orlando
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Probabilistic Graphical Models for
Classification
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Pedro Larrañaga,
Jose A. Lozano, Jose M. Peña, Iñaki Inza
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09:00 -
15:30 Workshop 7
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Libertas
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Parallel and Distributed Computing for
Machine Learning
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Rui Camacho, Ashwin
Srinivasan
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09:00 -
15:30 Workshop 8
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Sipun
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Discovery Challenge
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Petr Berka, Jan Rauch, Shusaku Tsumoto
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09:00 -
12:30 Tutorial 1
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Panorama
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KD Standards
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Sarab Anand, Marko
Grobelnik, Dietrich Wettschereck
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09:00 -
12:30 Tutorial 2
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Bobara
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Data Mining and Machine Learning in Time
Series Databases
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Eamonn Keogh
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14:00 -
15:30 Tutorial 3
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Panorama
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Exploratory
Analysis of Spatial Data and Decision Making Using Interactive Maps and
Linked Dynamic Displays
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Natalia Andrienko and
Gennady Andrienko
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14:00 -
15:30 Tutorial 4
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Bobara
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Music Data Mining
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Darrell Conklin
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16:00
- 17:15 KDNet Presentations and Exhibition
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Ragusa
and poster area
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17:30
Opening of ECML/PKDD-2003
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Ragusa
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17:45
Keynote talk
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Ragusa |
From Knowledge-based Systems to
Skill-based Systems: Sailing as a Machine Learning Challenge
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Pieter Adriaans
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18:45
Best paper awards announcement
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Ragusa |
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18:50
Best Student Paper
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Ragusa |
Logistic Model Trees
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Niels Landwehr, Mark Hall
and Eibe Frank
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20:00
Welcome Party
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Wednesday,
September 24
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09:00
Keynote talk
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Ragusa
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Taking Causality Seriously: Propensity
Score Methodology Applied to Estimate the Effects of Marketing
Interventions
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Donald Rubin
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10:00
Best PKDD Paper
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Ragusa
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Application of Inductive Logic Programming
to Structure-Based Drug Design
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David P. Enot and Ross D.
King
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10:30
Coffee Break
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11:00
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| 1a Text
Mining |
Ragusa
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| Explaining Text
Clustering Results using Semantic Structures |
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Andreas Hotho, Steffen Staab and Gerd Stumme |
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| A Simple Algorithm
for Topic Identification in 0-1 Data |
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| Jouni
K Seppanen, Ella Bingham and Heikki Mannila |
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| Topic Learning From
Few Examples |
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Huaiyu Zhu, Shivakumar Vaithyanathan and Mahesh Joshi |
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1b Ensemble
Methods
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Orlando
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A New Pairwise
Ensemble Approach for Text Classification
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Yan
Liu, Jaime Carbonell and Rong Jin
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On Boosting Improvement: Error Reduction
and Convergence Speed-Up
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Marc Sebban
and Henri-Maxime Suchier
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SMOTEBoost: Improving the Prediction of
Minority Class in Boosting
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Nitesh
Chawla, Aleksandar Lazarevic, Lawrence Hall and Kevin Bowyer
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1c Relational and
Multi-instance Learning
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Libertas
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Ensembles of Multi-Instance Learners
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Zhi-Hua Zhou
and Min-Ling Zhang
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A
Two-level Learning Method for Generalized Multi-Instance Problems
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Nils Weidmann, Eibe Frank and
Bernhard Pfahringer
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Mr-SBC: a Multi-Relational Naive Bayes
Classifier
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Michelangelo
Ceci, Annalisa Appice and Donato Malerba
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12:30
Lunch Break
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14:00
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2a Kernel Methods
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Ragusa
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Support Vector Machines with Example
Dependent Costs
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Ulf Brefeld,
Peter Geibel and Fritz Wysotzki
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Exploring Fringe Settings of SVMs for
Classification
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Adam
Kowalczyk and Bhavani Raskutti
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Classification Approach Towards Ranking
and Sorting
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Shyamsundar
Rajaram, Ashutosh Garg, Xiang Sean Zhou and Thomas Huang
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Color Image Segmentation: Kernel Do the
Feature Space
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Jianguo
Lee, Jingdong Wang and Changshui Zhang
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2b Probabilistic Models and Ranking
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Orlando
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On Decision Boundaries of Naive Bayes in
Continuous Domains
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Tapio Elomaa
and Juho Rousu
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Scaled CGEM: A Fast Accelerated EM
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Joerg Fischer
and Kristian Kersting
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A Skeleton-Based Approach to Learning
Bayesian Networks from Data
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Steven van
Dijk, Linda C. van der Gaag and Dirk Thierens
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Pairwise Preference Learning and Ranking
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Johannes
Furnkranz and Eyke Hullermeier
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2c Machine Learning
of Natural Language
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Libertas
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Backoff Parameter Estimation for the DOP
Model
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Khalil
Sima'an and Luciano Buratto
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Learning Rules to Improve a Machine
Translation System
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David Kauchak
and Charles Elkan
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Combined Optimization of Feature Selection
and Algorithm Parameters in
Machine Learning of Language
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Walter
Daelemans, Veronique Hoste, Fien De Meulder and Bart Naudts
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A Generative Model for Semantic Role
Labeling
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Cynthia
Thompson, Roger Levy and Christopher Manning
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16:00
Visit to the Walls of Dubrovnik
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Thursday, September 25
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top |
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09:00
Keynote Talk
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Ragusa
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Two-eyed Algorithms and Problems
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Leo Breiman
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10:00
Best ECML Paper
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Ragusa
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A Decomposition Of Classes Via Clustering
To Explain And Improve Naive Bayes
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Ricardo Vilalta and Irina
Rish
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10:30
Coffee Break
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11:00
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3a Decision Trees and
ROC Analysis
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Ragusa |
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Predicting Outliers
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Luis
Torgo and Rita Ribeiro
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Rademacher Penalization over Decision Tree
Prunings
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Matti
Kaariainen and Tapio Elomaa
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Volume Under the ROC Surface for
Multi-class Problems
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Cesar
Ferri, Jose Hernandez-Orallo and Miguel Angel Salido
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3b Information
Retrieval and Text Mining
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Orlando
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Life Cycle Modeling of News Events Using
Aging Theory
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| Chien
Chin Chen, Yao-Tsung Chen, Yeali Sun and Meng Chang Chen |
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Using Transduction and Multi-View Learning
to Answer Emails
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Michael
Kockelkorn, Andreas Luneburg and Tobias Scheffer
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Improving Rocchio with Weakly Supervised
Clustering
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Romain
Vinot and Francois Yvon
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3c Temporal Data Mining and Clustering
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Libertas
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Rule Discovery and Probabilistic Modeling
for Onomastic Data
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Antti
Leino, Heikki Mannila and Ritva Liisa Pitkanen
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An Indiscernibility-Based Clustering
Method with Iterative Refinement of Equivalent Relations
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Shoji
Hirano and Shusaku Tsumoto
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Discovering Unbounded Episodes in
Sequential Data
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| Gemma Casas |
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12:30
Lunch Break
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14:00
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4a
Personalization, Adaptivity and User Modeling
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Ragusa |
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Preference Mining: A
Novel Approach on Mining User Preferences for Personalized Applications
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Stefan Holland, Martin Ester and Werner Kiessling
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Collaborative
Filtering using Restoration Operators
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Atsuyoshi Nakamura, Mineichi Kudo and Akira Tanaka
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Towards Behaviometric
Security Systems: Learning to Identify a Typist
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Mordechai Nisenson, Ido Yariv, Ran El-Yaniv and Ron Meir
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4b Clustering
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Orlando
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Efficient Density Clustering Method for
Spatial Data
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Fei Pan,
Baoying Wang, Yi Zhang, Dongmei Ren, Xin Hu and William Perrizo
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Clustering in Knowledge Embedded Space
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Yungang
Zhang, Changshui Zhang and Shijun Wang
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Evaluation of Topographic Clustering and
its Kernelization
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Marie-Jeanne
Lesot, Florence d'Alche-Buc and Georges Siolas
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4c Computational
Learning Theory and Grammatical Inference
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Libertas
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Robust k-DNF Learning via Inductive Belief
Merging
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Frederic
Koriche and Joel Quinqueton
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Improvement of the State Merging Rule on
Noisy Data in Probabilistic Grammatical Inference
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Amaury
Habrard, Marc Bernard and Marc Sebban
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Unambiguous Automata Inference by Means of
State-merging Methods
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Francois
Coste and Daniel Fredouille
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15:30
Coffee Break
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16:00
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5a Reinforcement
Learning
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Ragusa |
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Iteratively
Extending Time Horizon Reinforcement Learning
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Damien
Ernst, Pierre Geurts and Louis Wehenkel
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A New Way to Introduce Knowledge into
Reinforcement Learning
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Pascal Garcia
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Optimising Performance of Competing Search
Engines in Heterogeneous Web Environments
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Rinat
Khoussainov and Nicholas Kushmerick
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5b Inductive Logic
Programming
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Orlando
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Bottom-Up Learning of Logic Programs for
Information Extraction from Hypertext Documents
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| Bernd Thomas |
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Enriching Relational Learning with Fuzzy
Predicates
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Henri Prade,
Gilles Richard and Mathieu Serrurier
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Efficient Frequent Query Discovery in
Farmer
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Siegfried
Nijssen and Joost Kok
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5c Preprocessing and
Visualization
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Libertas
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Analyzing Attribute Dependencies
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Aleks
Jakulin and Ivan Bratko
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Visualizations for Assessing Convergence
and Mixing of MCMC
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Jarkko
Venna, Samuel Kaski and Jaakko Peltonen
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Visualizing Class Probability Estimators
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Eibe Frank
and Mark Hall
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17:30
Coffee Break
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18:00
ECML/PKDD Community Meeting
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20:00
Conference Dinner
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Friday, September 26
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top |
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09:00
Keynote Talk
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Ragusa |
Next Generation Data Mining Tools: Power
Laws and Self-similarity for Graphs, Streams and Traditional Data
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Christos Faloutsos
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10:00
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6a Best Student Paper
Runner-up
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Ragusa
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Optimizing Local Probability Models for
Statistical Parsing
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Kristina
Toutanova, Mark Mitchell and Christopher Manning
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6b Relational Mining
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Orlando |
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Learning Characteristic Rules Relying on
Quantified Paths
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Teddy
Turmeaux, Ansaf Salleb, Christel Vrain and Daniel Cassard
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10:30
Coffee Break
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11:00
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7a Association Rules
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Ragusa
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Efficient Statistical Pruning of
Association Rules
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| Alan Ableson
and Janice Glasgow |
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Minimal k-Free Representations of Frequent
Sets
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Toon Calders
and Bart Goethals
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Majority Classification by means of
Association Rules
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| Elena Baralis
and Paolo Garza |
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7b Multi-agent
Reinforcement Learning
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Orlando
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COllective INtelligence with Sequences of
Actions
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Pieter Jan 't
Hoen and S.M. Bohte
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Extended Replicator Dynamics as a Key to
Reinforcement Learning in Multi-Agent Systems
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Karl Tuyls,
Dries Heytens, Ann Nowe and Bernard Manderick
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Self-Evaluated Learning Agent in Multiple
State Games
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Koichi
Moriyama and Masayuki Numao
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7c Preprocessing and
Postprocessing
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Libertas
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Experiments with Cost-sensitive Feature
Evaluation
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Marko
Robnik-Sikonja
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ExAnte: Anticipated Data Reduction in
Constrained Pattern Mining
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Francesco
Bonchi, Fosca Giannotti, Alessio Mazzanti and Dino Pedreschi
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The Pattern Ordering Problem
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Taneli
Mielikainen and Heikki Mannila
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12:30
Lunch Break
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14:00
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8a Text Classification
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Ragusa
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Text Categorisation Using Document
Profiling
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| Maximilien
Sauban and Bernhard Pfahringer |
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Using Belief Networks and Fisher Kernels
for Structured Document Classification
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Ludovic
Denoyer and Patrick Gallinari
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Improving SVM Text Classification
Performance through Threshold Adjustment
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James
Shanahan and Norbert Roma
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8b Reinforcement
Learning
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Orlando
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Abalearn: A Risk-Sensitive Approach to
Self-Play Learning in Abalone
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Pedro Campos
and Thibault Langlois
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Could Active Perception Aid Navigation of
Partially Observable Grid Worlds?
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Paul A. Crook
and Gillian Hayes
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Using MDP Characteristics to Guide
Exploration in Reinforcement Learning
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Bohdana
Ratitch and Doina Precup
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8c Constraints
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Libertas
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Adaptive Constraint Pushing in Frequent
Pattern Mining
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Francesco
Bonchi, Fosca Giannotti, Alessio Mazzanti and Dino Pedreschi
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Constraint-Based Mining of Sequential
Patterns over Datasets with Consecutive Repetitions
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Marion Leleu,
Christophe Rigotti, Jean-Francois Boulicaut and Guillaume Euvrard
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Improving Numerical Prediction With
Qualitative Constraints
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Dorian Suc
and Ivan Bratko
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15:30
Coffee Break
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16:00
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9a Decision Trees
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Ragusa
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Improving the AUC of Probabilistic
Estimation Trees
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| Cesar Ferri,
Peter Flach and Jose Hernandez-Orallo |
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Arbogodai, a New Approach for Decision
Trees
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Djamel A.
Zighed, Gilbert Ritschard, Walid Erray and Vasile-Marian Scuturici
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A Markov Network based Factorized
Distribution Algorithm for Optimization
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Roberto
Santana
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9b Mining Temporal and Clinical Data
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Orlando
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Automated Detection of Epidemics from the
Usage Logs of a Physicians' Reference Database
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Jaana Heino
and Hannu Toivonen
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Mining Multi-level Diagnostic Process
Rules from Clinical Databases using Rough Sets and
Medical
Diagnostic Model
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Shusaku
Tsumoto
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Efficiently Finding Arbitrarily Scaled
Patterns in Massive Time Series Databases
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Eamonn Keogh
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9c Preprocessing and
Clustering
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Libertas
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Ranking Interesting Subspaces for
Clustering High Dimensional Data
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Karin
Kailing, Hans-Peter Kriegel, Peer Kroger and Stefanie Wanka
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Symbolic Distance Measurements Based on
Characteristic Subspaces
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Marcus-Christopher
Ludl
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Statistical Sigma-partition Clustering
over Data Streams
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Nam Hun Park
and Won Suk Lee
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Overview