Mining Trajectory Databases via a Suite of Distance Operators

With the rapid progress of mobile devices and positioning technologies, Trajectory Databases (TD) have been in the core of database research during the last decade. Analysis and knowledge discovery in TD is an emerging field which has recently gained great interest. Extracting knowledge from TD using certain types of mining techniques, such as clustering and classification, impose that there is a mean to quantify the distance between two trajectories. Having as a main objective the support of effective similarity query processing, existing approaches utilize generic distance metrics that ignore the peculiarities of the trajectories as complex spatiotemporal data types. In this paper, we define a novel set of trajectory distance operators based on primitive (space and time) as well as derived parameters of trajectories (speed and direction). Aiming at providing a powerful toolkit for analysts who require producing distance matrices with different semantics as input to mining tasks, we ...

• Type: Conference
• Year: 2007
• Where: ICDE
• Authors: Nikos Pelekis, Ioannis Kopanakis, Irene Ntoutsi, Gerasimos Marketos, Yannis Theodoridis
• Keywords: Database, Generic Distance Metrics, ICDE 2007, Real Trajectory Datasets, Trajectory Distance Operators