In conjunction with
13th European Conference on Machine Learning (ECML'02)
6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'02)
19-23 August 2002
Workshop Topics and Goals
IDDM-2002 is as a follow-up to the successful IDDM-2001 workshop, which was held in conjunction with ECML/PKDD-2001 in Freiburg.
This workshop addresses the integration and collaboration aspects of Data Mining (DM), Decision Support (DS) and Meta-Learning (ML). In particular, this workshop is aimed at trying to upgrade the corresponding approaches and methodologies, such as CRISP-DM, through contributions, addressing the following issues:
Combining Data Mining with Decision
DM has the potential of solving DS problems, for example when previous decisions have been recorded as data to be used for analysis with DM tools. On the other hand, DS methodology usually results in a decision model, reflecting expert knowledge of decision makers. How can such expert knowledge be incorporated into problem solutions by DM? Can it be used as background knowledge in relational data mining? Can such expert knowledge be induced automatically? Are there any systematic methodological means of combining the two approaches to problem solving? How can DM benefit from DS models, especially in cases where the data available for mining is incomplete or of insufficient quality?
Collaborative Data Mining
Usually, DM tasks are solved by a single individual or group of individuals working jointly on a problem. However, with the Internet and advances of group support methodologies and tools, DM tasks could be solved through a collaboration of different groups of researchers at different sites. Novel ideas, reviews of existing approaches, or different modes of collaboration should be explored (e.g., competitive vs. collaborative), and issues addressed such as infrastructure and methods for supporting distant collaborative work (e.g., how to integrate new individuals/groups following the start/stop-any-time principle).
Combining Results of Classifiers, Meta-Learning,
Here, the emphasis is on novel ideas and/or reviews of existing approaches to model selection, model combination, model representation and all issues relevant to learning to learn (e.g., landmarking, performance prediction, knowledge transfer, data characterisation, meta-data collection and exploitation, standardised experimental setups/methods, etc).
Relational Data Mining
Most data in standard DM has the form of a single relational table. What if data is stored in multiple relational tables? Thus, how to combine the results of mining separate relational tables? A standard approach in ILP is to consider one table as the master data table, and all others as tables providing background knowledge. What if this is not natural? Would mining of individual tables and combining results be a better solution? Are there other approaches to this problem?
DM, DS, and ML Integration: Methodological,
Technical, and Standardization Aspects
This theme includes, but is not limited to, the following topics:
ML tools for classifier and model selection
ROC methodology for DM, DS and ML
Data pre-processing tools and methods for DM and DS
Representation languages for DM and DS models
Standards supporting the exchange of DM and DS models for different applications and visualization tools
PMML: Predictive Model Markup Language
DS shells that seamlessly integrate models developed by DM
Shared ontology and methodology for solving DM and DS problems
This workshop is aimed at both researchers and practitioners in Data Mining, Decision Support, and Meta-Learning. It is expected that there will be contributions from the main European research Consortia whose work focuses on the above topics (e.g., METAL, Sol-Eu-Net, KDNet, etc).
Participants will gain a better appreciation of the issues facing the application and deployment of DM, DS, and ML solutions in the real world. New ways of working together and combining results will be discussed, fostering further collaboration between participants' organisations. It is hoped that, as a result of this workshop, more people will work together more often, more effectively and in more sensible ways.
Papers are invited addressing one or more of the topics presented above. Papers should be prepared according to ECML/PKDD-2002 Instructions for Authors, and should not exceed 12 pages. Acceptable formats are PostScript or PDF.
Please send the papers by e-mail to
firstname.lastname@example.org, cc: email@example.com
Each paper will be reviewed by at least two reviewers. Accepted papers will be published in the workshop proceedings and on the Web.
Paper submission deadline: 24.05.2002
Paper acceptance notification: 14.06.2002
Paper camera-ready deadline: 01.07.2002
Workshop at ECML/PKDD-2002: 19.08.2002
Dunja Mladenic (firstname.lastname@example.org)
Nada Lavrac (email@example.com)
Jozef Stefan Institute
Phone: +386 1 477 33 09
Fax: +386 1 425 10 38
Hendrik Blockeel, Katholieke Universiteit Leuven, Belgium
Patrick Brezillon, University Paris VI, France
Ivan Bruha, McMaster University, Canada
Peter Flach, University of Bristol, United Kingdom
Dragan Gamberger, Rudjer Boskovic Institute, Croatia
Christophe Giraud-Carrier, ELCA Informatique SA, Switzerland
Salvatore Greco, University of Catania, Italy
Marko Grobelnik, Jozef Stefan Institute, Slovenia
Alipio Jorge, University of Porto, Portugal
Krzysztof Krawiec, Poznan University of Technology, Poland
Steve Moyle, Oxford University, United Kingdom
Vladislav Rajkovic, University of Maribor, Slovenia
Roman Slowinski, Poznan University of Technology, Poland
Jerzy Stefanowski, Poznan University of Technology, Poland
Maarten van Someren, University of Amsterdam, The Netherlands
Olga Stepankova, Czech Technical University, The Czech Republic
Ljupco Todorovski, Jozef Stefan Institute, Slovenia
Tanja Urbancic, Jozef Stefan Institute, Slovenia
Ricardo Vilalta, IBM T.J. Watson Research Center, USA
Takahira Yamaguchi, Shizuoka University, Japan
Blaz Zupan, University of Ljubljana, Slovenia