KDD-2001 Call for Participation
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/
On-line, interconnected systems offer unprecedented opportunities
for discovery and learning from the wealth of data they produce.
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.
The conference features tutorials, keynote addresses by
data-mining leaders in industry and academia, workshops, paper
and poster presentations from academia and industry, exhibits,
and the ever-popular KDD-CUP competition, where universities and
data mining companies compete to mine the best nuggets from real
data.
This year's agenda is not yet complete, but as an example of what
to expect, here are some highlights from last year's conference:
* over 900 attendees from over 30 countries
* five keynote addresses by CEO's of large software companies and
leading researchers
* standing-room-only tutorials and workshops
* over 20 exhibitors
* research papers on classification, association rules,
visualization, interactive knowledge exploration, mining the
web, etc.
* business papers on applications in marketing, manufacturing,
medicine, finance, aerospace, e-commerce, telephony, etc.
* a lively KDD-CUP competition with 35 competitors analysing data
from a web retail site to answer questions such as "Given a set
of page views, which product brand will the visitor view in the
remainder of the session?"
Please save the date and visit the website
http://www.acm.org/sigkdd/kdd2001/ for the most up-to-date
information about the conference.
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William H. Hsu, Ph.D.
Director, Lab for Knowledge Discovery in Databases
Assistant Professor of CIS, Kansas State University
Research Scientist, Automated Learning Group, NCSA
bhsu@cis.ksu.edu, bhsu@ncsa.uiuc.edu
http://www.cis.ksu.edu/~bhsu ICQ: 28651394
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