Temporal, spatial, and spatio-temporal data mining : first international workshop, TSDM 2000, Lyon, France, September 12, 2000 : revised papers
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 Ly...
Enregistré dans:
| Institution som forfatter: | |
|---|---|
| Andre forfattere: | , |
| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Serier: | Lecture notes in computer science. Lecture notes in artificial intelligence
2007 |
| Fag: | |
| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Temporal, spatial, and spatio-temporal data mining, first international workshop, TSDM 2000, Lyon, France, September 12, 2000, revised papers, John F. Roddick, Kathleen Hornsby (eds.), 2001, Berlin, Springer, 1 vol. (VI-163 p.), Lecture notes in computer science, 3-540-41773-7 • Temporal, Spatial, and Spatio-Temporal Data Mining, Texte imprimé, 9783662180976 |
Indholdsfortegnelse:
- 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.