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MobReduce: Reducing State Complexity of Mobility Traces

Hartmann, F.; Mayer, C.; Baumgart, I.

Abstract (englisch):
User traces are essential for analysis of human behavior and development of opportunistic networking protocols and applications. As user traces are collected with high granularity to apply them in diverse scenarios, they have a high complexity resulting from the large number of user states. We present MobReduce: a methodology for reducing the number of states in user traces. We apply MobReduce to individually to GPS locations and WiFi sightings of the Nokia Mobile Data Challenge data set and show how to trade off state complexity vs. granularity.


Zugehörige Institution(en) am KIT Institut für Telematik (TM)
Publikationstyp Proceedingsbeitrag
Jahr 2012
Sprache Englisch
Identifikator KITopen ID: 1000087133
Erschienen in Proceedings of the Nokia Mobile Data Challenge 2012 in connection with Pervasive 2012, Newcastle, UK, June 18-19, 2012
Verlag Newcastle University, UK
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