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                Call For Position Papers and Review Talks
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     Workshop on Research Issues on Data Mining and Knowledge Discovery
     		    in cooperation with ACM-SIGMOD'96 
               	 Montreal, Canada, June 2 (Sunday) 1996
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OBJECTIVES

Mining knowledge from large databases is a promising research area, with 
high application potential due to the huge amounts of data accumulated in 
databases and other repositories, coupled with the rapid growth of data.
Data mining has attracted people from many different fields, including 
database systems, knowledge-base systems, machine learning, knowledge 
acquisition, statistics, information retrieval, and data visualization.
The past conferences and workshops dedicated to knowledge discovery in 
databases are associated with AI conferences (e.g., IJCAI, AAAI, and Machine 
Learning).  It is important to have such a forum associated with database 
conferences as well to examine mining issues particularly related to database 
systems.  The objective of this workshop is to bring researchers in database 
systems together to discuss and examine the issues related to mining knowledge 
from databases.

FORMAT

The workshop will be held one day before the SIGMOD/PODS'96 conference.  
The plan is to have a full-day workshop, consisting of 3 theme sessions 
and one panel session.  The three theme sessions will be on three major 
issues: Foundations, Implementations, and Applications respectively.
Each theme session includes one overview talk, 5-6 position presentations
(including a short discussion after each position presentation).  If the 
number of submissions is large, we will consider arranging a poster session 
and a system demonstration session in parallel with it.  The workshop will 
also be coordinated with KDD'96 conference (http://www-aig.jpl.nasa.gov/kdd96)
(Portland, Oregon, August 1996).

TOPICS

The topics of the discussion will be partitioned into 3 major themes.

1. Foundations, principles and methodologies of data mining, including

	Knowledge discovery methods
	Efficiency and scalability of KDD algorithms
	Mining different kinds of knowledge from data
	Integration of deduction and induction techniques
	Statistics, probability and uncertainty in data mining
	Maintenance of mined knowledge and knowledge-base construction 
	Knowledge evolution through learning
	Methods for knowledge discovery in advanced database systems
	  (including object-oriented, deductive, spatial, temporal, textual, 
	  multimedia, heterogeneous, transaction, and active databases, and 
	  global information systems)

2. Systems and implementations for data mining, including

	Knowledge discovery systems, implementations, and performance
	Languages and interfaces for knowledge discovery in databases
	Interactive data mining and knowledge visualization
	Integrated discovery systems
	Systems, implementations, and performance for knowledge discovery 
	  in advanced database systems

3.  Knowledge discovery applications, including

	Successful knowledge discovery application examples in industry, 
	  administration, and business
	New application challenges and requirements for data mining
	The inadequacy of current knowledge discovery mechanisms
	Influence of data mining to the advances of database systems
	Security and social impact of data mining

SUBMISSION AND REVIEWS OF THE POSITION PAPERS and OVERVIEW TALK PAPERS.
 
Authors are invited to submit short position papers and comprehensive 
overview talk papers on each of the three themes.  Each position paper 
should be no longer than 6 pages.  Each overview talk paper should be
no longer than 25 pages.  WE ENCOURAGE ELECTRONIC SUBMISSIONS IN THE 
FORM OF POSTSCRIPT, LATEX, ETC. but limited to the std 8/5x11 size paper.
Each submitted paper will be reviewed by at least three program committee 
members.  The selected papers of the Workshop, after being extended into 
journal length and quality, will be considered for publication in a Special 
Issue of the Journal of Intelligent Information Systems (JIIS).

   
PROGRAM COMMITTEE
	  
Rakesh Agrawal, IBM Almaden Research Center, USA
Ron Brachman, AT&T Bell Laboratories, USA
Arbee L.P. Chen, National Tsing Hua University, Taiwan
Ming-Syan Chen, IBM T.J. Watson Research Center, USA
Wesley Chu, University of California at Los Angeles, USA
Son Dao, Hughes Research Labs, USA
Christos Faloutsos, AT&T and Univ. of Maryland, USA
Usama M. Fayyad, Jet Propulsion Lab, California Institute of Technology, USA
Randy Goebel, University of Alberta, Canada
Howard Hamilton, University of Regina, Canada
Jiawei Han, Simon Fraser University, Canada
Tomasz Imielinski, Rutger University, USA
Larry Kerschberg, George Mason University, USA 
Willi Kloesgen, GMD, Germany 
Hans-Peter Kriegel, University of Munich, Germany
Laks V.S. Lakshmanan, Concordia University, Canada
Hongjun Lu, National University of Singapore, Singapore
Heikki Mannila, University of Helsinki, Finland
Sham Navathe, Georgia Institute of Technology, USA
Raymond Ng, University of British Columbia, Canada
KayLiang Ong, Trilogy, USA
Gregory Piatetsky-Shapiro, GTE Laboratories, USA
Ramakrishnan Srikant, IBM Almaden Research Center, USA
Bhavani Thuraisingham, Mitre Corp., USA.
Shalom Tsur, Argonne National Research Lab, USA
S.K. Michael Wong, University of Regina, Canada
Carlo Zaniolo, University of California at Los Angeles, USA

IMPORTANT DATES
 
	Submissions Due: January 15, 1996
	Acceptance Notice: March 15, 1996
	Final Version due: April 15, 1996

Five hard copies or one electronic copy of the paper should be submitted
by January 15, 1996 to

	Dr. Raymond Ng
	Department of Computer Science
	University of British Columbia 
	Vancouver, B.C., V6T 1Z4, Canada
	rng@cs.ubc.ca

ORGANIZING COMMITTEE

Jiawei Han, Simon Fraser University, Canada (han@cs.sfu.ca).
Laks V.S. Lakshmanan, Concordia University, Canada (laks@cs.concordia.ca).
Raymond Ng, University of British Columbia, Canada (rng@cs.ubc.ca).

Workshop (SIGMOD'96 DMKD) Home Page: http://fas.sfu.ca/cs/conf/dmkd96.html