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|Title:||Privacy-aware knowledge discovery from location data||Authors:||Atzori, M.
|Issue Date:||2007||Source:||8th International Conference on Mobile Data Management, MDM 2007, 7 May 2007 through 11 May 2007, Mannheim, 72930||Abstract:||Spatio-temporal, geo-referenced datasets are growing rapidly, and will be more in the near future. This phenomenon is mostly due to the daily collection of telecommunication data from mobile phones and other location-aware devices and is expected to enable novel classes of applications based on the extraction of behavioral patterns from mobility data. Such patterns could be used for instance in traffic and sustainable mobility management (e.g., to study the accessibility to services), urban planning, environmental monitoring, and collaborative location-based services. Clearly, in these applications privacy is a concern, since some knowledge may be sensitive, or an over-specific pattern may reveal the behaviour of groups of few individual. In this paper we focus on automated privacy-preserving methods we developed for extracting and sharing user-consumable forms of knowledge from large amounts of raw data referenced in space and in time. ©2007 IEEE.||URI:||https://doi.org/10.1109/MDM.2007.59
|Appears in Collections:||Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering|
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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