Spatio-temporal data mining for location-based services

Abstract

Abstract Largely driven by advances in communication and information technology, s uch as the increasing availability and accuracy of GPS technology and the miniaturiza tion of wireless communication devices, Location–Based Services (LBS) are con tinuously gaining popularity. Innovative LBSes integrate knowledge about the use rs into the service. Such knowledge can be derived by analyzing the location data o f users. Such data contain two unique dimensions, space and time , which need to be analyzed. The objectives of this thesis are three–fold. First, to extend popular data min ing methods to the spatio–temporal domain. Second, to demonstrate the usefulness of the extended methods and the derived knowledge in two promising LBS examples. Fi- nally, to eliminate privacy concerns in connection with spatio–temporal data minin g by devising systems for privacy–preserving location data collection and min ing