Workshop 1
Chairs: Pavel Brazdil
and
Alipio Jorge,
University of Porto, Portugal
email: pbrazdil@ncc.up.pt
amjorge@ncc.up.pt
Deadline : July 17th, 2000
Title: Data Mining, Decision Support, Meta-learning and ILP:
Forum for Practical Problem
Presentation and Prospective Solutions Time.
Description :
The objective is to provide a forum for interchange of ideas between
researchers and representatives of companies involved in applying the existing
technologies in solving of real problems. Researchers will describe their
experience in applying the methodologies to problems of commercial, industrial
and social interest. The representatives of companies will describe not
only their success stories, but also concerns about the directions the
research should follow.
Website: http://www.ncc.up.pt/~ltorgo/ML_group.htmls/Events/DDMI/ |
Workshop 2
Chairs: John F. Roddick, Flinders U., South Australia
and
Kathleen Hornsby, U.Maine, USA
email: roddick@cs.flinders.edu.au,
khornsby@spatial.maine.edu
Deadline : June 15th, 2000
Title: PKDD Workshop on Temporal, Spatial and Spatio-Temporal
Data Mining (TSDM2000)
Description :
The workshop will focus on research and practice of knowledge discovery
from datasets containing explicit or implicit temporal or spatial information.
Main topics of the workshop are: temporal association rule mining, time
and space-oriented sequence mining,temporal and spatial classification,
mining from geographic and geo-referenced data, spatial data mining, spatial
clustering methods, spatio-temporal data mining, KDD processes and frameworks
specifically catering for temporal and spatial data mining.
Website: http://www.spatial.maine.edu/TSDM2000/TSDM2000.html |
Workshop 3
Chairs:Jan Komorowski, Norwegian University of Science andTechnology,
Trondheim, Norway
email:Jan.Komorowski@idi.ntnu.no
Deadline : August 14th, 2000
Title:Knowledge Discovery in Biology.
Description :
The advent of high throughput screening, e.g. the so-called microarray
technology, opens up for large-scale data acquisition from biological
system experiments. New approaches and tools are required to support
knowledge extraction from these large information pools. The goal of
workshop is both to attract the attention of the KDD community to the
challenges raised by biological research and to make the biologists
aware of possible solutions that may be provided by the KDD field.
Website: http://www.idi.ntnu.no/~janko/KnowledgeDiscoveryInBiology.html |
Workshop 4
Chairs:Hugo Zaragoza, LIP6, University Paris 6, France
Patrick Gallinari, LIP6, University Paris 6, France
Martin Rajman, EPFL, Switzerland
email: Hugo.Zaragoza@lip6.fr
Patrick.Gallinari@lip6.fr
Martin.Rajman@epfl.ch
Deadline July 10th, 2000
Title:Machine Learning and Textual Information Access
Description :
As "Textual Information Access" we denote here both the emerging
interdisciplinary community of researchers from different fields
sharing interest in the textual data objects and machine or
statistical learning techniques aiming to develop automatic text
analysis systems. Among the main topics are: information retrieval
and filtering, multi-media information access, topic detection and
tracking, text summarisation, representation techniques of textual
information semantics, etc.
Website: http://www-connex.lip6.fr/mltia2000.html
|
Workshop 5
Chairs: Jean-Louis Ermine, CEA Paris, France
email: ermine@cartier.cea.fr
Deadline : July 10th , 2000
Title:Knowledge Management: Theory and Applications
Description :
Knowledge management is the process of extracting knowledge from the
sources accessible to persons in an organisation (structured data in
databases, semi-structured data on the web and company documents,
unstructured data in the brain of persons, multimedia data). The
following topics are involved: knowledge capture, knowledge
synthesis, knowledge dissemination, models and methodologies for
knowledge management, etc.
Website:http://www.sciences.univ-nantes.fr/irin/KMTA2000/
|
Workshop 6
Chair: Edwin Diday, University of Paris Dauphine, 75016 France
email: diday@ceremade.dauphine.fr
Deadline : June 30th , 2000
Title: Symbolic Data Analysis: Theory, Software and Applications for Knowledge Mining
Description :
In many domains of human activities huge sets of data are now recorded in large data bases.
Summarising these data by their underlying concepts (regions, towns or socio-demographic groups
as unemployment type in Official statistics, species of insects in biology, kind of failures in industrial
companies, scenario of accidents in road trafic, etc.) in order to extract knowledge, becomes a
leading task. To describe these concepts, instead of standard units, more complex data called
"symbolic data" are needed. "Symbolic data" happen not only in order to summarise huge sets of
data but also from many other sources where internal variation of the units and structural data
appear. As "Symbolic Data Analysis" we denote an emerging interdisciplinary community of
researcher coming from Official Statistics, classification and Data Analysis techniques. Among the
main topics are: how to extract these symbolic data from huge data bases, how to implement,
analyse and visualise them, how to model concepts in their intent and their extent by "symbolic
objects", how to disseminate them, etc.
The Symbolic Data Analysis theory* is now enhanced by a prototype software tool called "SODAS"
which results from the effort of 17 European teams sponsored by EUROSTAT. This new software
is able first: to extract concepts from a data base, second: to analyse them. It will be presented and
discussed in a tutorial training during the afternoon. The ISO-3D European consortium whose aim
is to develop a Symbolic Data Analysis system with
3-D graphics, sound animation and temporal symbolic data, will also be presented and discussed.
Submissions :
The prospective participants interested to give a
presentation concerning applications should contact the organizers by 30
June 2000.
Written submissions are required by 30 June
Acceptance notices will be sent by 15 July.
Final versions are due by 15 August.Workshop KDD.
Program: HTML version or PDF version
|