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Daqing Zhang
Researcher at Peking University
Publications - 355
Citations - 20924
Daqing Zhang is an academic researcher from Peking University. The author has contributed to research in topics: Context (language use) & Mobile computing. The author has an hindex of 67, co-authored 331 publications receiving 16675 citations. Previous affiliations of Daqing Zhang include Institut Mines-Télécom & Institute for Infocomm Research Singapore.
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Journal ArticleDOI
Mobility prediction in telecom cloud using mobile calls
TL;DR: This article investigates the large-scale user mobility traces that are collected by a telecom operator, and finds that mobile call patterns are highly correlated with the co-location patterns at the same cell tower at the the same time.
Journal ArticleDOI
Providing real-time assistance in disaster relief by leveraging crowdsourcing power
Dingqi Yang,Daqing Zhang,Korbinian Frank,Patrick Robertson,Edel Jennings,Mark Roddy,Michael Lichtenstern +6 more
TL;DR: A crowdsourcing disaster support platform aimed at efficiently harnessing crowdsourcing power to provide those on-site rescue staff with real-time remote assistance and achieve good usability is designed and developed.
Journal ArticleDOI
Disorientation detection by mining GPS trajectories for cognitively-impaired elders
TL;DR: The iBDD method is developed that is able to detect two categories of outlying trajectories in a uniform framework in real-time and can achieve 95% detection rate of disorientation with less than 3% of false positives, based on properly chosen parameters.
Journal ArticleDOI
GeeAir: a universal multimodal remote control device for home appliances
TL;DR: By combining diverse interaction techniques in a single device, the GeeAir enables different user groups to control home appliances effectively, satisfying even the unmet needs of physically and vision-impaired users while maintaining high usability and reliability.
Proceedings ArticleDOI
PrivCheck: privacy-preserving check-in data publishing for personalized location based services
TL;DR: The key idea of PrivCheck is to obfuscate user check-in data such that the privacy leakage of user-specified private data is minimized under a given data distortion budget, which ensures the utility of the obfuscated data to empower personalized LBSs.