Information visualization in data mining and knowledge discovery
Information visualization in data mining and knowledge discovery
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach
Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach
A Visualization System for Space-Time and Multivariate Patterns (VIS-STAMP)
IEEE Transactions on Visualization and Computer Graphics
Exploratory spatio-temporal data mining and visualization
Journal of Visual Languages and Computing
International Journal of Geographical Information Science
A clustering-based data reduction for very large spatio-temporal datasets
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
A new hybrid clustering method for reducing very large spatio-temporal dataset
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
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High-resolution spatio-temporal datasets are being collected every day to record the behaviour of several natural phenomena. However, data-mining techniques are needed to extract relevant patterns from very large repositories and reveal spatial and temporal patterns in the behaviour of these phenomena. To this aim, we propose a system for mining data with spatial and temporal characteristics, and for visualizing and interpreting the results. Within this system, we have developed two complementary 3D visualization environments, one based on Google Earth and one relying on a Java3D graphical user interface. In this paper, we illustrate the main features of the system we have developed, and report on the main results we have obtained by analysing the Hurricane Isabel dataset.