RWTH Aachen University
The increasing amount of mobile phones that are equipped with localization technology offers a great opportunity for the collection of mobility data. This data can be used for detecting mobility patterns. Matching mobility patterns in streams of spatiotemporal events implies a trade-off between efficiency and pattern complexity. Existing paper deals either with low expressive patterns, which can be evaluated efficiently, or with very complex patterns on powerful machines. The authors propose an approach which solves the trade-off and is able to match flexible and sufficiently complex patterns while delivering a good performance on a resource-constrained mobile device.