Identifying Users by Asynchronous Mobility Trajectories
| Autor: | Zhongyuan Wang, Qi Mengjun, Tao Lu, Zheng He |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0303 health sciences
Similarity (geometry) Computer science Probabilistic logic 02 engineering and technology Similarity measure computer.software_genre 03 medical and health sciences Identification (information) Asynchronous communication 020204 information systems 0202 electrical engineering electronic engineering information engineering Trajectory Data mining computer 030304 developmental biology |
| Zdroj: | IGARSS |
| DOI: | 10.1109/igarss.2019.8898556 |
| Popis: | With the popularity of location-based services and applications, a large amount of mobility data has been generated. Identity recognition through mobile trajectory information, especially asynchronous trajectory data has arisen great concerns in social security prevention and control. This paper advocates an identification resolution method based on the most frequently distributed TOP-N regions regarding user trajectories. This method first finds TOP-N regions whose trajectory points are most frequently distributed so as to reduce the computational complexity. It then combines probabilistic deviation and angle cosine to calculate TOP-N region similarity between two trajectories to identify the same user. We conducted extensive experiments on two real GPS trajectory datasets GeoLife and Cabspotting and comprehensively discussed the experimental results. The experimental results show that this method is substantially effective and efficiency for user identification. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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