Time-Series Data Mining in a Geospatial Decision Support

13 years 5 months ago

Download www.digitalgovernment.org

This paper presents an overview of the motivation for, and the use of time-series data mining in, a Geospatial Decision Support System (GDSS). Our approach is based on a combination of time-series data mining algorithms and spatial interpolation techniques. The initial focus of the system is to facilitate drought risk management. We develop two association rule mining algorithms and two interpolation methods, which help drought experts predict local weather conditions or potential yield impact based on the global weather patterns.

Dan Li, Sherri K. Harms, Steve Goddard, William J.

Real-time Traffic

Data Mining Algorithms | DGO 2003 | DGO 2007 | Mining Algorithms | Time-series Data Mining |

claim paper

» 3D Visualization of Multiple Time Series on Maps

» Visually mining and monitoring massive time series

» On the need for time series data mining benchmarks a survey and empirical demonstration

» A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision S...

» Mining the Future Predicting Itemsets Support of Association Rules Mining

» Semisupervised learning with data calibration for longterm time series forecasting

» Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features

» A Probabilistic Approach to Fast Pattern Matching in Time Series Databases

Post Info
More Details (n/a)

Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2003
Where	DGO
Authors	Dan Li, Sherri K. Harms, Steve Goddard, William J. Waltman, Jitender S. Deogun

Comments (0)

Sciweavers

Time-Series Data Mining in a Geospatial Decision Support

Data Mining Algorithms | DGO 2003 | DGO 2007 | Mining Algorithms | Time-series Data Mining |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers