Workshop on Symbolic Data Analysis

["Rosanna Verde" <Rosanna.Verde@tin.it>]

Cari Colleghi,
ho il piacere di annunciarvi il Workshop su "Symbolic Data Analysis" che si
terra' nel prossimo mesi di luglio a Cracovia.
Per ulteriori informazioni potete contattarmi al seguente indirizzo di posta
elettronica:
rosanna.verde@unina2.it

Cordiali saluti e auguri di buon Natale e felice Anno
Rosanna Verde



*********       C A L L   F O R    P A P E R S         *********

Workshop

S y m b o l i c    D a t a    A n a l y s i s

CRACOW (Poland) -  Monday, 15th  July 2002


SCIENTIFIC PROGRAM COMMITTEE
-         International Members -
H. Bacelar-Nicolau (Portugal), V. Batagelj (Slovenia), L. Billard (USA),
H-H. Bock (Germany),  C. Bravo (Spain), P. Brito (Portugal),
F.A.T. De Carvalho (Brazil), E. Diday (France), M. Chavent (France),
F. Esposito (Italy), M. Gettler-Summa (France), K.S. Gowda (India),
A.Hardy (Belgium), M. Ichino (Japan), C. Lauro (Italy),
Y. Lechevallier (France), D. Malerba (Italy), C. Marcelo (Portugal),
M.Noirhomme (Belgium), F. Palumbo (Italy), H. Papageorgiou (Greece),
J.P. Rasson (Belgium), R. Verde (Italy),  S. Winsberg (USA).

ORGANIZING COMMITTEE
Rosanna Verde - Second University of Naples, Italy - (chair)
Paula Brito - University of Porto, Portugal
Francisco de A.T. de Carvalho - Federal University of Pernambuco, Brazil
Andrzej Sokolowski - University of Cracow, Poland - (local organizer)

TOPIC

Symbolic Data Analysis (SDA) is a new domain in the area of knowledge
discovery and data management, related to multivariate analysis,
pattern recognition, data bases and artificial intelligence. SDA allows a
more
realistic description of the input units by taking into consideration their
internal
variation and their complex structure. SDA provides a better explanation of
its results by an automatic interpretation which is closer to the users
natural
language. SDA  provides tools suitable for managing complex, aggregated,
relational, and higher-level data described by multi-valued variables, where
the entries of a data table are sets of categories, intervals, or
probability
distributions, which are usually related by logical rules and taxonomies.
The methodological issues under development generalise the classical
exploratory
 data analysis techniques, like visualisation, factorial techniques,
decision tree,
discrimination, regression, neuronal methods, multidimensional scaling,
classification
and clustering methods as well as conceptual lattices.

The aim of this workshop is to present new theoretical results and
applications
in this framework.

Researchers interested in SDA are invited to submit an abstract (max 2 pages
- following the guidelines that can be found at the IFCS2002 web site:
http://ifcs2002.ae.krakow.pl ) by e-mail to rosanna.verde@unina2.it
in PDF format (please send it as .ZIP file).

Deadlines and Time schedule
- March 1st, 2002 - Deadline submission abstract
- March 31th, 2002 - Notification of the acceptance of the abstract

WorkshopSDA.pdf