A privacy-preserving semantic annotation framework using online social media

Abstract

© Springer International Publishing AG, part of Springer Nature 2018. Semantic annotation framework that allows enriching locations or trajectories with semantic abstractions of the raw spatiotemporal data benefits understanding the semantic behavior of moving objects. Existing semantic annotation approaches mainly analyze specific parts of a trajectory, e.g. stops, in association with data from 3rd party geographic sources, e.g. (POI) points-of-interest, road networks. However, these semantic resources are static thus miss important dynamic event information. Recent location-based social networking provides a new dynamic and prevalent source of human activity data that can be a potential se..