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Temporal, Spatial, and Spatio-Temporal Data Mining: First International Workshop TSDM 2000 Lyon, France, September 12, 2000 Revised Papers / Edition 1
by John F. Roddick
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Temporal, Spatial, and Spatio-Temporal Data Mining, TSDM 2000, held in Lyon, France in September 2000 during the PKDD 2000 conference.
The ten revised full papers presented are complemented by an introductory workshop report and an updated bibliography for the
Overview
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Temporal, Spatial, and Spatio-Temporal Data Mining, TSDM 2000, held in Lyon, France in September 2000 during the PKDD 2000 conference.
The ten revised full papers presented are complemented by an introductory workshop report and an updated bibliography for the emerging new field; this bibliography is organized in nine topical chapters and lists more than 150 entries. All in all, the volume reflects the state of the art in the area and sets the scene for future R & D activities.
Product Details
- ISBN-13:
- 9783540417736
- Publisher:
- Springer Berlin Heidelberg
- Publication date:
- 02/28/2001
- Series:
- Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence Series, #2007
- Edition description:
- 2001
- Pages:
- 172
- Product dimensions:
- 5.92(w) x 8.84(h) x 0.41(d)
Table of Contents
Workshop Report - International Workshop on Temporal, Spatial, and Spatio-temporal Data Mining - TSDM2000.- Discovering Temporal Patterns in Multiple Granularities.- Refined Time Stamps for Concept Drift Detection During Mining for Classification Rules.- K-Harmonic Means -A Spatial Clustering Algorithm with Boosting.- Identifying Temporal Patterns for Characterization and Prediction of Financial Time Series Events.- Value Range Queries on Earth Science Data via Histogram Clustering.- Fast Randomized Algorithms for Robust Estimation of Location.- Rough Sets in Spatio-temporal Data Mining.- Join Indices as a Tool for Spatial Data Mining.- Data Mining with Calendar Attributes.- AUTOCLUST+: Automatic Clustering of Point-Data Sets in the Presence of Obstacles.- An Updated Bibliography of Temporal, Spatial, and Spatio-temporal Data Mining Research.
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