• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Semantic Trajectory Based Behavior Generation for Groups Identification

Vol. 12, No.12, December 31, 2018
10.3837/tiis.2018.12.010, Download Paper (Free):

Abstract

With the development of GPS and the popularity of mobile devices with positioning capability, collecting massive amounts of trajectory data is feasible and easy. The daily trajectories of moving objects convey a concise overview of their behaviors. Different social roles have different trajectory patterns. Therefore, we can identify users or groups based on similar trajectory patterns by mining implicit life patterns. However, most existing daily trajectories mining studies mainly focus on the spatial and temporal analysis of raw trajectory data but missing the essential semantic information or behaviors. In this paper, we propose a novel trajectory semantics calculation method to identify groups that have similar behaviors. In our model, we first propose a fast and efficient approach for stay regions extraction from daily trajectories, then generate semantic trajectories by enriching the stay regions with semantic labels. To measure the similarity between semantic trajectories, we design a semantic similarity measure model based on spatial and temporal similarity factor. Furthermore, a pruning strategy is proposed to lighten tedious calculations and comparisons. We have conducted extensive experiments on real trajectory dataset of Geolife project, and the experimental results show our proposed method is both effective and efficient.


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Cite this article

[IEEE Style]
Yang Cao, Zhi Cai, Fei Xue, Tong Li and Zhiming Ding, "Semantic Trajectory Based Behavior Generation for Groups Identification," KSII Transactions on Internet and Information Systems, vol. 12, no. 12, pp. 5782-5799, 2018. DOI: 10.3837/tiis.2018.12.010

[ACM Style]
Cao, Y., Cai, Z., Xue, F., Li, T., and Ding, Z. 2018. Semantic Trajectory Based Behavior Generation for Groups Identification. KSII Transactions on Internet and Information Systems, 12, 12, (2018), 5782-5799. DOI: 10.3837/tiis.2018.12.010