KDD 2001 Workshop on Temporal Data Mining

To be held in conjunction with the

7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001)

August 26, 2001, San Francisco, CA, USA

WORKSHOP PROGRAM

 From  To Author Title
9:00 am 9:10 Unnikrishnan and Uthurusamy Introduction
9:10 10:00 Srikant Invited talk: Sequential patterns, trends and privacy
10:00 10:30 Break + Poster Session
10:30 11:00 Presentation of Poster Previews
10:30 10:35 Kusiak Data farming methods for temporal data mining
10:35 10:40 Li, Ning, Wang, Jajodia Generating market basket data with temporal information
10:40 10:45 Lin, Orgun, Williams Multilevels hidden markov models for temporal data mining
10:45 10:50 Lin, Yun, Chen Utilizing slice scan and selective hash for episode mining
10:50 10:55 Fu, Chung, Ng, Luk Pattern discovery from stock time series using self-organizing maps
10:55 11:00 Joshi, Karypis, Kumar A universal formulation of sequential patterns
11:00 11:20 Antunes, Oliveira Temporal data mining: an overview
11:20 11:40 Chudova, Smyth Unsupervised identification of sequential patterns under a markov assumption
11:40 12:00 Gehrke Mining and monitoring sensor networks
12:00 pm  1:30 Lunch Break + Poster Session
1:30 1:50 Leonard Large-scale automatic forecasting: millions of forecasts
1:50 2:10 Tan, Steinbach, Kumar, et al. Finding spatio-temporal patterns in earth science data
2:10 2:30 Han, Pei Pattern growth methods for sequential pattern mining: principles and extensions
2:30 2:50 Martin, Yohai Data mining for unusual movements in temporal data
2:50 3:10 Yu, Goldberg, Bi Time series forecasting using wavelets with predictor-corrector boundary treatment
3:10 4:00 Agrawal, Kumar, Mannila, Smyth, U&U Panel: Challenges in temporal data mining
Bibliography Roddick, Hornsby, Spiliopoulou YABTSSTDMR - Yet Another Bibliography of Temporal, Spatial and Spatio-Temporal Mining Research

Call for Papers

Much of the data contained in large databases has explicit or implicit temporal information. In spite of this, most of the data mining techniques tend to look for static relationships within the data. The aim of this workshop is to critically evaluate the need for temporal data mining and identify promising technologies and methodologies for doing the same.

Topics of interest include:

Paper submission:

Authors are invited to submit papers related to above topics. We encourage submissions that describe significant contributions to these areas as well as research that are at an early stage. We welcome survey, state-of-the-art, and position papers as well as papers that describe significant applications, software, systems, and solutions. Papers should be about 12 pages. An abstract and complete contact information should be included in a cover page. Please submit electronic copies to unni@gmr.com or samy@gm.com. Hardcopies can be submitted to:

K.P. Unnikrishnan
General Motors R&D Center
MC 480-106-359,
Warren, MI 48090-9055, USA

Deadlines:

June 15, 2001 Submission of papers

July 01, 2001 Notification of acceptance

July 16, 2001 Final version of accepted papers due

Workshop Co-Chairs:

K. P. Unnikrishnan
General Motors R&D Center
Phone: 810-986-1450, Fax: 810-986-0574
unni@gmr.com

Ramasamy Uthurusamy
General Motors IS&S
Phone: 313-667-4669, Fax: 313-667-4616
samy@gm.com

Program committee:

Usama Fayyad, DigiMine
Padhraic Smyth, University of California, Irvine
Vipin Kumar, University of Minnesota
Heikki Mannila, Helsinki University of Technology
C Lee Giles, Pennsylvania State University
Jia-Wei Han, University of Illinois