How to tell an airport from a home
Published 20 October 2010
Andreas Pitsillidis, Yinglian Xie, Fang Yu, Martı́n Abadi, Geoffrey M. Voelker, Stefan Savage
Citations5
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TL;DR
The preliminary results suggest that rough location categories such as residences, workplaces, and travel venues can be accurately inferred, enabling a range of potential applications from demographic analyses to ad specialization and security improvements.
Abstract
Today's Internet services increasingly use IP-based geolocation to specialize the content and service provisioning for each user. However, these systems focus almost exclusively on the current position of users and do not attempt to infer or exploit any qualitative context about the location's relationship with the user (e.g., is the user at home? on a business trip?). This paper develops such a context by profiling the usage patterns of IP address ranges, relying on known user and machine identifiers to track accesses over time. Our preliminary results suggest that rough location categories such as residences, workplaces, and travel venues can be accurately inferred, enabling a range of potential applications from demographic analyses to ad specialization and security improvements.
Keywords
Social SciencesComputer Science
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