Spatio-temporal data mining in ecological and veterinary epidemiology

Spatio-temporal data mining in ecological and veterinary epidemiology

Understanding the spread of any disease is a highly complex and interdisciplinary exercise as biological, social, geographic, economic, and medical factors may shape the way a disease moves through a population and options for its eventual control or eradication. Disease spread poses a serious threat in animal and plant health and has implications for ecosystem functioning and species extinctio...

Spatio-temporal statistics: applications in epidemiology, veterinary medicine and ecology.

Exploratory spatio-temporal data mining and visualization

Spatio-temporal data sets are often very large and difficult to analyze and display. Since they are fundamental for decision support in many application contexts, recently a lot of interest has arisen toward data-mining techniques to filter out relevant subsets of very large data repositories as well as visualization tools to effectively display the results. In this paper we propose a data-mini...

Mining Spatio-Temporal Patterns in Trajectory Data

Spatio-temporal patterns extracted from historical trajectories of moving objects reveal important knowledge about movement behavior for high quality LBS services. Existing approaches transform trajectories into sequences of location symbols and derive frequent subsequences by applying conventional sequential pattern mining algorithms. However, spatio-temporal correlations may be lost due to th...

Rough Sets in Spatio-temporal Data Mining

In this paper I define spatio-temporal regions as pairs consisting of a spatial and a temporal component and I define topological relations between them. Using the notion of rough sets I define approximations of spatio-temporal regions and relations between those approximations. Based on relations between approximated spatio-temporal regions configurations of spatio-temporal objects can be char...