A survey on deep learning for human mobility

M Luca, G Barlacchi, B Lepri… - ACM Computing Surveys …, 2021 - dl.acm.org
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …

PrivCheck: Privacy-preserving check-in data publishing for personalized location based services

D Yang, D Zhang, B Qu, P Cudré-Mauroux - Proceedings of the 2016 …, 2016 - dl.acm.org
With the widespread adoption of smartphones, we have observed an increasing popularity
of Location-Based Services (LBSs) in the past decade. To improve user experience, LBSs …

Venice through the lens of Instagram: A visual narrative of tourism in Venice

L Rossi, E Boscaro, A Torsello - … of the The Web Conference 2018, 2018 - dl.acm.org
The last decade has seen a huge expansion in the use of social media to extract data about
human behaviour. While metadata and textual information have taken the lion's share as …

Geographic differential privacy for mobile crowd coverage maximization

L Wang, G Qin, D Yang, X Han, X Ma - Proceedings of the AAAI …, 2018 - ojs.aaai.org
For real-world mobile applications such as location-based advertising and spatial
crowdsourcing, a key to success is targeting mobile users that can maximally cover certain …

Understanding the potential risks of sharing elevation information on fitness applications

Ü Meteriz, NF Yιldιran, J Kim… - 2020 IEEE 40th …, 2020 - ieeexplore.ieee.org
The extensive use of smartphones and wearable devices has facilitated many useful
applications. For example, with Global Positioning System (GPS)-equipped smart and …

Quantifying privacy loss of human mobility graph topology

D Manousakas, C Mascolo… - Proceedings on …, 2018 - discovery.ucl.ac.uk
Human mobility is often represented as a mobility network, or graph, with nodes
representing places of significance which an individual visits, such as their home, work …

DART: De-Anonymization of personal gazetteers through social trajectories

M Francia, E Gallinucci, M Golfarelli… - Journal of Information …, 2020 - Elsevier
The interest in trajectory data has sensibly increased since the widespread of mobile
devices. Simple clustering techniques allow the recognition of personal gazetteers, ie, the …