[With apologies for multiple copies]
FIRST CALL FOR PAPERS
IDDM-2002
2nd International Workshop on
Integration and Collaboration Aspects of
Data Mining, Decision Support and Meta-Learning
http://ecmlpkdd.cs.helsinki.fi/iddm-2002.html
This workshop will be held in conjunction with ECML/PKDD-2002, Helsinki,
Finland, 19-23 August, 2002 (http://ecmlpkdd.cs.helsinki.fi/). It is a
follow-up to the successful IDDM-2001 workshop held in Freiburg (see
http://www.cs.bris.ac.uk/~cgc/ECML-PKDD01/cfp.html).
Workshop Topics and Goals
=========================
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 Support
- -------------------------------------------
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, etc.
- -----------------------------------------------------
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, such as
PMML (Predictive Model Markup Language)
- - DS shells that seamlessly integrate models developed by DM
- - Shared ontology and methodology for solving DM and DS problems
Intended Audience
=================
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.
Paper Submission
================
Papers are invited addressing one or more of the topics presented above.
Papers should be prepared according to ECML/PKDD-2002 Instructions for
Authors (http://ecmlpkdd.cs.helsinki.fi/ifa.html), and should not exceed
12 pages. Acceptable formats are PostScript or PDF.
Please send the papers by e-mail to
marko.bohanec@ijs.si, cc: branko.kavsek@ijs.si
Each paper will be reviewed by at least two reviewers. Accepted papers
will be published in the workshop proceedings and on the WWW.
Important Dates
===============
Paper submission: 24 May 2002
Notification of acceptance: 14 June 2002
Camera-ready version: 1 July 2002
Workshop at PKDD/ECML 2002: 19 or 20 August 2002 (to be announced)
Workshop Chairs
===============
Marko Bohanec (marko.bohanec@ijs.si)
Dunja Mladenic (dunja.mladenic@ijs.si)
Nada Lavrac (nada.lavrac@ijs.si)
Jozef Stefan Institute
Jamova 39
SI-1000 Ljubljana
Slovenia
Phone: +386 1 477 33 09
Fax: +386 1 425 10 38
Program Committee
=================
Hendrik Blockeel, Katholieke Universiteit Leuven, Belgium
Patrick Brezillon, University Paris VI, France
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
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