Data Mining Lessons Learned

Description

Journal, conference and workshop papers seldom report on failures, yet reported failures are crucial for increasing awareness of which approach to use in which situations. At conferences we often hear of successful applications, but we rarely hear of steps leading to success, steps that failed, and representation choices that were critical to success. In addition, papers rarely include expert evaluations of results. The purpose of this workshop is to assemble data mining practitioners and to gather experience from successful and unsuccessful data mining endeavors. We seek to learn from successes (evaluated by domain experts) and, most importantly, from failed data mining endeavors (why was an approach not successful, what can dataminers learn from this experience). The main aim is to start gathering the lessons learned.

Links

Call for Papers

Proceedings (all papers on-line)

Schedule

Important Dates

Organizers

Nada Lavrac	Hiroshi Motoda	Tom Fawcett
J. Stefan Institute	Osaka University	HP Laboratories
Slovenia	Japan	USA

Program committee

Marko Bohanec	Andrea Danyluk
Charles Elkan	Dragan Gamberger
Christophe Giraud-Carrier	Ross King
Huan Liu	Dunja Mladenic
Foster Provost	Patricia Riddle
Maarten van Someren	Ashwin Srinivasan
Einoshin Suzuki	Shusaku Tsumoto