News

  KDD-2001: The Seventh ACM SIGKDD International Conference on
  Knowledge Discovery and Data Mining
      August 26-29, 2001, San Francisco, CA, USA

  Register online at http://www.acm.org/sigkdd/kdd2001/

KDD-2001, the premier annual data mining conference organized by the
scientists and practitioners who popularized data mining in the mid
1990's, is a must-attend conference, featuring state-of the art keynote
talks, free tutorials by experts from academia and industry, rigorously
selected technical and industrial papers, the KDD-Cup data mining
competition, and more.

Highlights of the conference this year include:

* Keynote presentations by leaders in the field on collaboration,
  knowledge discovery in biology, and more!
* Industrial track invited talks on mining e-commerce data,
  recommendation systems, predictive modeling, and more
* Tutorials -- free with the registration! -- featuring e-business,
  frequent-pattern mining, outlier analysis, value-based mining,
  mobile data mining, and advances in decision trees
* KDD-Cup 2001: results from this year's genomics and drug design
  competition
* Workshops on visualization, multimedia, scientific data, weblog
  analysis, bioinformatics, and temporal data
* Panels on sampling, data mining startup companies, and new research
  directions
* Exhibits from over 26 leading software & hardware vendors and
  academic projects
* Technical paper presentations from 20 authors, plus 32 poster
  presentations giving attendees a chance to talk directly with the
  authors
* Industry track papers presented by 12 teams from leading companies
  such as Microsoft, IBM, Verizon, and others -- learn how the most
  successful companies put data mining into practice!

See the conference schedule and full details at
http://www.acm.org/sigkdd/kdd2001 and register online by following the
links from the conference homepage.

With the first-rate program summarized above, there is something for
everyone at KDD-2001 and you won't want to miss this once-a-year
opportunity to meet and share knowledge with your data-mining
colleagues from around the world.

James Louis,
www.kddresearch.org
Computing and Information Sciences Department,
Kansas State University.