KDD-2001 Final Call for Papers
          The Seventh ACM SIGKDD International Conference on
                 Knowledge Discovery and Data Mining
                               KDD-2001

              August 26-29, 2001, San Francisco, CA, USA

                  http://www.acm.org/sigkdd/kdd2001/

                              Due Dates:
                     Paper Abstracts February 26
                         Submissions March 2

            See also Calls for Industrial Track papers and
        Workshop, Panel, and Tutorial proposals on the Website

On-line, interconnected systems offer unprecedented opportunities for
discovery and learning from the wealth of accompanying data.
Extracting useful knowledge from such data is becoming more difficult,
as volume and complexity push traditional techniques beyond their
limits. Knowledge Discovery and Data Mining (KDD) techniques automate
the process of extracting knowledge from data. The annual ACM SIGKDD
conference brings together researchers and practitioners focusing on
new developments and challenges in KDD brought about by this data
explosion.

Suggested Paper Topics include (but are not limited to): 

Methods and Algorithms: data mining, web mining, text mining, mining
time-series data, mining mixed-type data, mining high-dimensional
data, incorporating domain knowledge, open-ended discovery, scalable
algorithms, statistical methods, unconventional knowledge
representations.

The KDD Process: process modeling, process automation, data cleaning,
human involvement, visualization, interactive exploration,
interestingness, evaluating knowledge and discoveries.

Integrated Systems: embedded KDD techniques, unification of mining
with database architectures, integration of data
mining/warehousing/OLAP, exploration and discovery systems.

Applications and Experiences: e-commerce, privacy issues,
personalization, activity monitoring, scientific applications,
benchmarks, new application areas, tools, commercial successes or
failures.


Paper Submission 

Papers should describe original work that has not appeared and is not
under review elsewhere (specialized workshops excluded). Both basic
and applied research papers are solicited, as well as papers
describing applications making significant research
contributions. Paper length should be a maximum of 20 pages, using
12pt. font, 1.5 line spacing, and 1in. margins. We strongly encourage
electronic submission of papers.  An electronic abstract of at most
250 words must be submitted by Feb 26, 2001.

See http://www.acm.org/sigkdd/kdd2001/IT/FAQ.html for guidance on
whether to submit a paper to the research or industrial track.


Other SIGKDD-2001 Calls for Papers / Proposals:

Call for Industrial Track papers (due March 2)
        http://www.acm.org/sigkdd/kdd2001/IT/ 
Call for Tutorial Proposals (due March 7)
        http://www.acm.org/sigkdd/kdd2001/Tutorials/ 
Call for Panel Proposals (due March 7)
        http://www.acm.org/sigkdd/kdd2001/Panels/ 

  
KDD-2001 Organizing Committee:

General Chair:             Mario Schkolnick, SGI  
Program Chairs:            Foster Provost, NYU 
                           Ramakrishnan Srikant, IBM Almaden  
Industrial Session Chairs: Vasant Dhar, NYU  
                           Surajit Chaudhuri, Microsoft Research  
Best Paper Awards Chair:   Jiawei Han, Simon Fraser University  
Conference Treasurer:      Ian Davidson, SGI  
Sponsorship Chairs:        Robert Grossman, Magnify
                           Michael Blasgen, Blasgen.com
Demos/Exhibits Chair:      Paul Bradley, digiMine
Registration Chair:        Jeonghee Yi, IBM Research
Local Arrangements Chair:  Archana Sathaye, San Jose State University  
Panels Chair:              Pedro Domingos, Univ. of Washington  
Publicity Chair:           George John, E.piphany  
Tutorials Chair:           Tom Fawcett, HP Labs  
Workshops Chair:           Roberto Bayardo, IBM Almaden 
Webmaster:                 T.S. Lim, Recursive Partitioning 
SIGKDD Chair:              Won Kim, Cyber Database Solutions 

Program Committee: http://www.acm.org/sigkdd/kdd2001/pc.html 


_____________________________________________________
George H. John              xenon.stanford.edu/~gjohn
Data Mining Guru, E.piphany          www.epiphany.com






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