On querying and mining semantic-aware mobility timelines

Abstract

(1): [23][24][25][26][27][28][29][30][31][32] 2013), in this paper, we present a unified framework for the management and the analysis of LifeSteps, i.e., data objects about human mobility including both (raw) spatio-temporal trajectories and their semantic counterpart. In particular, we provide solutions for developing real-world semantic-aware moving object database and trajectory data warehouse systems and we devise respective query processing algorithms. Our experimental study on realistic synthetic data including synchronized raw (i.e., GPS log) and semantic (i.e., diaries) information verifies the effectiveness and efficiency of the proposed framework. This paper is an extended version of the DSAA'2015 Long Presentation paper "Hermes sem : a Semantic-aware Framework for the Management and Analysis of our LifeSteps" [14]. Source code, datasets etc. for Hermes sem and Hermoupolis are available at

Reverse Nearest Neighbor Search in Semantic Trajectories for Location-Based Services

“…There is a significant commercial and research interest in spatial keyword queries over semantic trajectories [19], [32]. Similar to [2], we classify the existing indexes on semantic trajectories into three categories according to the combination scheme: loose combination, spatial-first combination, and text-first combination.…”