Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

This SpringerBrief provides an overview within data mining of spatiotemporal frequentpattern mining from evolving regions to the perspective of relationshipmodeling among the spatiotemporal objects, frequent pattern miningalgorithms, and data access methodologies for mining algorithms. Whilethe focus of this book is to provide readers insight into the miningalgorithms from evolving regions, the authors also discuss datamanagement for spatiotemporal trajectories, which has becomeincreasingly important with the increasing volume of trajectories. This brief describes state-of-the-art knowledge discoverytechniques to computer science graduatestudents who are interested in spatiotemporal data mining, as well asresearchers/professionals, who deal with advanced spatiotemporal dataanalysis in their fields. These fields include GIS-experts, meteorologists,epidemiologists, neurologists, and solar physicists.