Publications

GUEST EDITORS:

Hillol Kargupta
University of Maryland, Baltimore County
hillol@cs.umbc.edu

Sanghamitra Bandyopadhyay
Indian Statistical Institute
sanghami@isical.ac.in

Byung-Hoon Park
Oak Ridge National Laboratory
parkbh@ornl.gov


CONTENTS

Guest Editorial - H. Kargupta, S. Bandyopadhyay and B. H. Park

NOTE: Advances in computing and communication over wired and wireless
networks have resulted in many pervasive distributed computing
environments. These environments often come with different distributed
sources of data and computation. Mining in such environments naturally
calls for proper utilization of these distributed resources. Moreover, in
many privacy sensitive applications different, possibly multiparty, data
sets collected at different sites must be processed in a distributed
fashion without collecting everything to a single central site. However,
most off-the-shelf data mining systems are designed to work as a
monolithic centralized application which does not work well in many of the
emerging distributed, ubiquitous, possibly privacy-sensitive data mining
applications. Distributed data mining (DDM) offers an alternate approach
to address this problem of mining data using distributed resources. This
special section offers an interesting blend of papers that deals with
several emerging DDM concepts and techniques.

For more information, see

http://www.mail-archive.com/inductive@listserv.unb.ca/msg00937.html