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A Privacy Enhanced Crowdsourcing Architecture for Road Information Mining Using Smartphones

Roth, Christian and Kesdogan, Dogan (2018) A Privacy Enhanced Crowdsourcing Architecture for Road Information Mining Using Smartphones. IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA), pp. 17-24.

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Other URL: https://ieeexplore.ieee.org/document/8599574/


Abstract

The digitization of our road and traffic systems enables evermore advanced location based services to support us in our everyday tasks with prominent examples being navigation applications like Google Maps or speed camera directories like TomTom Speed Cameras. The information collection that lies at the base of these applications however is often either done behind closed doors, or relies on the ...

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Item type:Article
Date:November 2018
Additional Information (public):Conference 20-22 Nov. 2018 Paris, France, France
Institutions:Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik IV (Prof. Dr. Doğan Kesdoğan)
Identification Number:
ValueType
10.1109/SOCA.2018.00010DOI
Keywords:Privacy, Crowdsourcing, Navigation, Data Mining, Smartphone
Dewey Decimal Classification:000 Computer science, information & general works > 004 Computer science
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:38056
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