DM: CFP: KDD-99

[foster]

                           Call for Papers

        KDD-99: The ACM SIGKDD Fifth International Conference
                on Knowledge Discovery and Data Mining

                August 15-18, 1999, San Diego, CA, USA
            http://research.microsoft.com/datamine/kdd99/

                            Sponsored by:
          Association for Computing Machinery (ACM) - SIGKDD
                           Co-sponsored by:
                   AAAI, ACM SIGMOD, and ACM SIGART




The continuing rapid growth of on-line data and the widespread use of
databases necessitate the development of techniques for extracting
useful knowledge and for facilitating database access. The challenge
of extracting knowledge from data is of common interest to several
fields, including statistics, databases, pattern recognition, machine
learning, data visualization, optimization, and high-performance
computing. KDD-99 will focus on techniques, applications, and
experiences, bringing together researchers and practitioners.

Starting this year, the KDD series will represent the annual
conferences of the newly formed SIGKDD--the ACM Special Interest Group
on Knowledge Discovery and Data Mining.

                               --------
                               Calendar
                               --------

             Electronic abstracts due:  March 1, 1999 
                      Submissions due:  March 5, 1999 

 Notification of acceptance/rejection:  May 17, 1999  
              Camera-ready copies due:  June 14, 1999 


Submission Guidelines: Please see the KDD-99 web site for detailed
instructions (http://research.microsoft.com/datamine/KDD99).  All
submissions (including research papers, panels, demos, tutorials and
industrial track submissions) must be received by March 5, 1998.
Prospective authors are encouraged to submit research papers on any
topics of relevance to knowledge discovery and data mining.  In
addition to fundamental research, we solicit papers fostering
cross-fertilization and interdisciplinary integration, as well as
papers that describe significant experiences and implementation
lessons. Topics of interest include, but are not limited to:

KDD Techniques             Human Interaction and the KDD Process      
    
--- ----------             ----- ----------- --- --- --- -------      
         
New KDD algorithms         Data and knowledge visualization           
     
Mining the Web             Evaluating knowledge and potential 
discoveries  
Text/multimedia            Interactive exploration                    
     
Data cleaning/noisy data   Visualizing large, high-dimensional data   
     
Incremental algorithms      
High-dimensional data
Background knowledge                 Mining Enterprise Databases      
   
                                      ------ ---------- ---------     
    
Implementation and Applications      Scalable algorithms              
   
-------------- --- ------------      Unification of mining with 
querying 
Implementation & use of KDD systems  Database architectures for KDD   
         
Vertical applications                Database primitives for KDD      
   
Case studies: success/failure        Integration: 
mining/warehousing/OLAP
Benchmarks                           
                                     

KDD-99 Organization
--- -- ------------
Program Committee Co-Chairs: Surajit Chaudhuri 
(SurajitC@microsoft.com) 
                             David Madigan 
(madigan@stat.washington.edu)

General Chair: Usama Fayyad (Fayyad@microsoft.com)

Awards: G. Piatetsky-Shapiro (gps@kstream.com)
Demos/Exhibits: Ismail Parsa (iparsa@epsilon.com)
Industrial/Applications Track: Jim Gray (gray@microsoft.com)
                               Ronny Kohavi (ronnyk@bluemartini.com)
Local Arrangements: Jenny Zhang (jgz@hnc.com)
Panels: Padhraic Smyth (smyth@ics.uci.edu)
Proceedings: Kyuseok Shim (shim@research.bell-labs.com)
Publicity: Foster Provost (provost@acm.org)
Sponsorship: Ramasamy Uthurusamy (samy@iss.gm.com)
Tutorials: Jiawei Han (han@cs.sfu.ca)
Workshops: Rakesh Agrawal (ragrawal@almaden.ibm.com)