Temporal, Spatial, and Spatio-Temporal Data Mining

1. Front Matter

   Pages I-I

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2. Workshop Report - International Workshop on Temporal, Spatial, and Spatio-temporal Data Mining - TSDM2000

   • Kathleen Hornsby

   Pages 1-4

3. Discovering Temporal Patterns in Multiple Granularities

   • Yingjiu Li, X. Sean Wang, Sushil Jajodia

   Pages 5-19

4. Refined Time Stamps for Concept Drift Detection During Mining for Classification Rules

   • Ray J. Hickey, Michaela M. Black

   Pages 20-30

5. K-Harmonic Means -A Spatial Clustering Algorithm with Boosting

   • Bin Zhang, Meichun Hsu, Umesh Dayal

   Pages 31-45

6. Identifying Temporal Patterns for Characterization and Prediction of Financial Time Series Events

   • Richard J. Povinelli

   Pages 46-61

7. Value Range Queries on Earth Science Data via Histogram Clustering

   • Ruixin Yang, Kwang-Su Yang, Menas Kafatos, X. Sean Wang

   Pages 62-76

8. Fast Randomized Algorithms for Robust Estimation of Location

   • Vladimir Estivill-Castro, Michael E. Houle

   Pages 77-88

9. Rough Sets in Spatio-temporal Data Mining

   • Thomas Bittner

   Pages 89-104

10. Join Indices as a Tool for Spatial Data Mining

    • Karine Zeitouni, Laurent Yeh, Marie-Aude Aufaure

    Pages 105-116

11. Data Mining with Calendar Attributes

    • Howard J. Hamilton, Dee Jay Randall

    Pages 117-132

12. AUTOCLUST+: Automatic Clustering of Point-Data Sets in the Presence of Obstacles

    • Vladimir Estivill-Castro, Ickjai Lee

    Pages 133-146

13. An Updated Bibliography of Temporal, Spatial, and Spatio-temporal Data Mining Research

    • John F. Roddick, Kathleen Hornsby, Myra Spiliopoulou

    Pages 147-163

14. Back Matter

    Pages 165-165

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This volume contains updated versions of the ten papers presented at the First International Workshop on Temporal, Spatial and Spatio-Temporal Data Mining (TSDM 2000) held in conjunction with the 4th European Conference on Prin- ples and Practice of Knowledge Discovery in Databases (PKDD 2000) in Lyons, France in September, 2000. The aim of the workshop was to bring together experts in the analysis of temporal and spatial data mining and knowledge discovery in temporal, spatial or spatio-temporal database systems as well as knowledge engineers and domain experts from allied disciplines. The workshop focused on research and practice of knowledge discovery from datasets containing explicit or implicit temporal, spatial or spatio-temporal information. The ten original papers in this volume represent those accepted by peer review following an international call for papers. All papers submitted were refereed by an international team of data mining researchers listed below. We would like to thank the team for their expert and useful help with this process. Following the workshop, authors were invited to amend their papers to enable the feedback received from the conference to be included in the ?nal papers appearing in this volume. A workshop report was compiled by Kathleen Hornsby which also discusses the panel session that was held.

• DOM
• Discovery Science
• Geographic Information Processing
• Knowledge Discovery
• Knowledge Engineering
• Spatial Data Mining
• Spatial Information Processing
• Spatio-Temporal Data Mining
• Temporal Data Mining
• algorithms
• classification
• data mining
• geographic data

• School of Informatics and Engineering, Flinders University of South Australia, Adelaide, South Australia

  John F. Roddick

• National Center for Geographic Information and Analysis, University of Maine, Maine, USA

  Kathleen Hornsby

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