Workshop on Research Issues in Data Mining and Knowledge Discovery
DMKD 2001
http://www.cs.cornell.edu/johannes/dmkd2001.htm
Santa Barbara, CA -- May 20th, 2001
In conjunction with the ACM
SIGMOD/PODS 2001 Conference
Funding for this workshop has been provided by IBM Research.
PRELIMINARY WORKSHOP PROGRAM
(Online version of the papers can be found at the end of this page.)
9:00
DMKD Opening and Invited Talk: “Crossing the Analytical-Chasm:
Applying Data Mining Successfully.” Brian Lent, President and CEO,
Intelligent Results, Inc.
10:00-10:50
First paper session
- Padhraic
Smyth. Breaking Out of the
Black-Box: Research Challenges in Data Mining.
- Jian
Pei, Anthony K.H. Tung, and Jiawei Han. Fault-Tolerant Frequent Pattern
Mining: Problems and
Challenges.
10:50-11:00
Short Coffee Break
11:00-12:40
Second paper session
- Baohua
Gu, Bing Liu, Feifant Hu, and Huan Liu. Efficiently Determine the Starting
Sample Size for Progressive Sampling.
- Xiong
Wang. Mining Protein Surfaces.
- George
Kollios, Stan Sclaroff and Margrit Betke. Motion Mining: Discovering Spatio-Temporal Patterns in Databases of
Human Motion.
- Qin
Ding, William Perizo, Qiang Ding, and Amalendu Roy. On Mining Satellite and
Other Remotely Sensed Images.
12:40-2:00
Lunch break
2:00-3:00
Invited talk: Title "An
Industry Perspective on DMKD Research Issues".
Ramasamy Uthurusamy, General Motors.
3:00-3:30
Coffee break
3:30-4:45
Third paper session
- Minos
Garofalakis and Rajeev Rastogi. Data Mining Meets Network Management:
The NEMESIS Project.
- Pedro
Domingos and Geoff Hulten. Catching Up with the Data:
Research Issues in Mining Data Streams.
- Jochen
Hipp, Ulrich Guntzer, and Udo Grimmer. Data Quality Mining - Making a Virtue
of Necessity.
4:45
Closing remarks and end of workshop
WORKSHOP OBJECTIVES
The Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD)
was started five years ago to foster discussion and investigation of data mining
research issues pertinent to large databases and data warehouses. Over these
years, data mining as a discipline has matured considerably. Particularly strong
progress has been made in the design of scalable algorithms that transform the
oceans of bits in very large databases into interpretable patterns and
predictive models.
This year's sixth DMKD workshop is aimed at discussing the next generation of
data mining research, with the goal of bringing together researchers and
experienced practitioners from academia and industry. The atmosphere of the
workshop will be informal, fostering interaction through short presentations and
open discussion of new research visions and industrial experiences. The workshop
is being held in cooperation with SIGMOD/PODS 2001.
TOPICS OF INTEREST
- New applications of data mining
- Industrial experiences with data mining projects
- Limitation of the current generation of data mining tools
- Intersection of data mining with other disciplines
- Research visions: Where is data mining in 2010?
SUBMISSION GUIDELINES
Papers should be no more than six pages. The workshop accepts only electronic
submission of papers in ASCII, HTML, PDF, or PostScript format to either of the
two workshop chairs (bayardo@almaden.ibm.com
or johannes@cs.cornell.edu).
Accepted papers will be included in the informal proceedings made available to
the workshop attendees and online.
IMPORTANT DATES
- Submission deadline: April 2, 2001
- Notification: April 23, 2001
- Camera-ready due: May 7, 2001
- Workshop: May 20, 2001
REGISTRATION
There is no separate registration fee for the workshop; registration is included
in the SIGMOD/PODS 2001 registration.
STUDENT TRAVEL SCHOLARSHIPS
Limited amount of funding is available for travel expenses for student
participants in the workshop. Priority will be given to students who are
(co-)authors of accepted papers in the workshop. To apply for student
scholarships, send email to Roberto Bayardo or Johannes Gehrke by April 30.
WORKSHOP CHAIRS
PROGRAM COMMITTEE
- Paul Bradley, digiMine Inc.
- Charu C. Aggarwal, IBM T. J. Watson Research Center.
- Dimitrios Gunopulos, UCR.
- Martin Ester,
University of Munich.
- Venkatesh Ganti,
Microsoft Research.
- Minos Garofalakis, Bell
Laboratories.
- Jiawei Han, Simon Fraser
University.
- Bing Liu, National
University of Singapore.
- Heikki Mannila. Nokia Research Center.
- Flip Korn, AT&T Labs
-- Research.
- Vipin Kumar. University of
Minnesota.
- Sharad Mehrotra, University of California.
- Sridhar Ramaswamy, Epiphany.
- Kyuseok Shim, KAIST.
- Mohammed J. Zaki, Rensselaer
Polytechnic Institute.
ACCEPTED PAPERS ONLINE:
FULL
PAPERS:
- Minos
Garofalakis and Rajeev Rastogi.
Data
Mining Meets Network Management: The
NEMESIS Project.
- Padhraic
Smyth. Breaking
Out of the Black-Box: Research Challenges in Data Mining
- Jian
Pei, Anthony K.H. Tung, and Jiawei Han.
Fault-Tolerant
Frequent Pattern Mining:
Problems
and Challenges.
- Baohua
Gu, Bing Liu, Feifant Hu, and Huan Liu.
Efficiently
Determine the Starting Sample Size for Progressive
Sampling.
- Jochen
Hipp, Ulrich Guntzer, and Udo Grimmer.
Data
Quality Mining - Making a Virtue of Necessity.
- David
Skalak. Speed-up Mining or "Why is data
mining iterative?"
- Qin
Ding, William Perizo, Qiang Ding, and Amalendu Roy.
On Mining
Satellite and Other Remotely Sensed Images.
- Pedro
Domingos and Geoff Hulten. Catching
Up with the Data: Research
Issues in Mining Data Streams.
- George
Kollios, Stan Sclaroff and Margrit Betke.
Motion
Mining: Discovering
Spatio-Temporal
Patterns in Databases of Human Motion.
- Xiong
Wang. Mining Protein
Surfaces.
POSITION
PAPERS: