Weka-STPM: from trajectory samples to semantic trajectories

Enormous quantities of trajectory data are collected from many sources, as GPS devices and mobile phones, as sequences of points. These data can be used in many application domains such as traffic management, urban planing, tourism, and bird migration. However, in most applications a higher level of abstraction should be used instead of sample points. In this paper we present an extension of the classical open source data mining toolkit Weka to support automatic trajectory data preprocessing in order to mining trajectories in a higher abstraction level. We propose Weka-STPM which is interoperable with all databases constructed under OGC specifications. We tested Weka-STPM with geographic databases and trajectory data stored into Postgresql/PostGIS, which is an open source GDBMS implemented according to OGC standards.