Clustering - Special Aspects
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ABSTRACT
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Clustering presents many difficult problems. 
With few exceptions, almost all interesting 
problems are NP-complete and require 
approximative solutions. We discuss some of 
these challenges. The usefulness of 
clustering in highlighting the structure 
of a set of objects is contemplated and the 
notion of data clusterability is introduced 
and recent results concerning clusterability 
are presented.
          
SPEAKER(S)
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SIMOVICI Dan, Professor, PhD
Professor of Computer Science
University of Massachusetts, Department of Computer Science
Boston
S.U.A.
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Dr.Dan Simovici has been Professor of Computer Science at University
of Massachusetts Boston USA since 1985.His research focuses on
information-theoretical methods in data mining, semantic models
in databases and algebraic aspects of multiple-valued logic.Dr.Simovici
held several research and teaching positions at University of
Science and Technology, Lille, France, Tohoku University, Sendai,
Japan, and University of Miami, Florida.He is also an editor
of several scientific journals (e.g., Journal for Multiple-Valued
Logic and Soft Computing, International Journal for Parallel,
Emergent, and Distributed Systems, International Journal for
Software and Information Technologies, etc.).Dr.Simovici completed
his PhD in 1974 at the University of Bucharest, Romania, his
M.S. in Mathematics in 1970 at the Al. I. Cuza University of
Iasi, Romania and his M.S. in E.E. in 1965 at the Polytechnical
Institute of Iasi, Romania.
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