VDM@ECML/PKDD2001
International Workshop on Visual Data
Mining
4 September 2001
in conjunction with
ECML/PKDD2001
- 2th European Conference on Machine Learning (ECML'01) and 5th European
Conference on Principles and Practice of Knowledge Discovery in Databases
(PKDD'01), 3-7 September, 2001
John W. Tukey emphasized that seeing may be
believing or disbelieving, but above all, data analysis involves visual,
as well as statistical, understanding. Perhaps the most famous and certainly
one of the oldest visual explanations in mathematics is the visual proof
of the Pythagorean theorem. This proof is unusual in its brevity and its
complete appropriateness to the problem. Pictures and diagrams are also used
in non-geometrical parts of mathematics, mostly for psychological reasons:
harnessing our ability to reason "visually" with the elements of a diagram
in order to assist our more purely logical or analytical thought processes.
Thus, a visual reasoning approach to the area of data mining and machine
learning promises to overcome some of the difficulties experienced in the
comprehension of the information encoded in data sets and the models derived
by other quantitative data mining methods.
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Last updated: 16-Jan-2002
Download: Call for papers
(PDF)
Download: Proceedings
(PDF)
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| Visual data mining is a collection of
interactive reflective methods that support exploration of data sets by
dynamically adjusting parameters to see how they affect the information being
presented. This emerging area in explorative and intelligent data analysis
and mining is based on the integration of concepts from computer graphics,
visualisation metaphors and methods, information and scientific data
visualisation, visual perception, cognitive psychology, diagrammatic reasoning,
visual data formatting and 3D collaborative virtual environments for information
visualisation. It offers machine learning and data mining community powerful
means of analysis that can assist in uncovering patterns and trends that
are likely to be missed with other non-visual methods. Visual data mining
techniques offer the luxury of being able to make observations without
preconception.
The goal of the workshop is to provide a forum
for presentation and discussion of the newest both mature and greenhouse
ideas, research and developments in the methods and techniques for visual
data mining and to identify the short- and long-term research directions
in the field.
TOPICS OF INTEREST
The scope of the workshop covers the intersection
of broad range of disciplines. The major topics of the workshop include but
are not limited to:
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visual methods for data analysis
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multimedia support for visual reasoning in
data mining
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visualisation schemata and formal visual
representation of metaphors
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visual explanations
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general visual data mining process models
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visual reasoning and uncertainty management
in data mining
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complexity, efficiency and scalability of
information visualisation in data mining
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incorporation of domain knowledge in visual
reasoning
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virtual environments for data visualisation
and exploration
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algorithmic animation methods for visual data
mining
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perceptual and cognitive aspects of information
visualisation in data mining
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interactivity and iterativity in visual data
mining
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representation of discovered knowledge
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visual analysis of large databases
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collaborative visual data exploration and
model building
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metrics for evaluation of visual data mining
methods
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generic system architectures and prototypes
for visual data mining
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methods for visualising semantic content
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immersive data mining techniques
We also encourage submissions, which present
early stages of research work, software applications and demonstrations.
SUBMISSIONS
We encourage submissions of 10-15 pages. Contact
author and email address should be specified. Electronic submissions in either
PDF, PS, RTF or Microsoft Word Document format are preferable. Please, e-mail
electronic submissions to
vdm-chairs@it.uts.edu.au with
subject "VDM@PKDD2001 Submission". If not submitting an electronic version,
please send a hard copy original to one of the workshop chairs.
DISSEMINATION
Peer-reviewed submissions, accepted for
presentation at the workshop will be published in the workshop proceedings.
Extended and revised paper-oriented versions of selected submissions will
be published in a book by Springer-Verlag or Kluwer Academic Publishers.
IMPORTANT DATES
| Submission
deadline: |
8 June 2001 |
| Acceptance notification: |
29 June 2001 |
| Camera ready copy: |
13 July 2001 |
| Workshop day: |
4 September 2001 |
WORKSHOP CHAIRS
PROGRAM COMMITTEE
| James L. Alty |
Loughborough University, UK |
| Heinz-Dieter Boecker |
GMD National Research Center for Information
Technology, Germany |
| Chaomei Chen |
Brunel University, UK |
| Di Cook |
Iowa State University, USA |
| John Debenham |
University of Technology Sydney,
Australia |
| Alberto Del Bimbo |
Universitá degli Studi di Firenze,
Italy |
| Edwin Diday |
Université Paris IX - Dauphine,
France |
| Chitra Dorai |
IBM Thomas J. Watson Research, USA |
| Alex Duffy |
University of Strathclyde, UK |
| Erik Granum |
Aalborg University, Denmark |
| Georges Hebrail |
EDF R&D, France |
| Maolin Huang |
University of Technology Sydney,
Australia |
| Alfred Inselberg |
Multidimensional Graph Ltd, Israel |
| Daniel A. Keim |
University of Konstanz, Germany |
| Carlo Lauro |
University of Naples, Italy |
| Torsten Möller |
Simon Fraser University, Canada |
| Bruce Thomas |
University of South Australia,
Australia |
| Carl H. Smith |
University of Maryland, USA |
| Masaki Suwa |
Chukyo University, Japan |
| Osmar R. Zaïane |
University of Alberta, Canada |
| Ahmed Zighed |
Universite Lumiere Lyon, France |
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