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Automatic derivation of context descriptions

 
: Jung, Christian; Feth, Denis; Elrakaiby, Yehia

:

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society:
IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support, CogSIMA 2015. Proceedings : March 9-12, 2015, Orlando, Florida
Los Alamitos: IEEE Computer Society, 2015
ISBN: 978-1-4799-8015-4
S.70-76
International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA) <2015, Orlando/Fla.>
Englisch
Konferenzbeitrag
Fraunhofer IESE ()
context awareness; security; mobile device; context description

Abstract
Context-awareness in mobile information systems bears a huge potential. However, context-awareness is still in its infancy and its full potential is not yet exploited. One reason is the poorly supported creation and learning of suitable context descriptions. Another problem is the questionable predictive power of context descriptions that makes it difficult to correctly determine the current user context. For applications that depend on the user context, the reliable determination of the context is essential. In this paper, we propose a process to characterize contexts. We correlate raw contextual information with user activities to determine accurate context descriptions. In a case study, we show how different statistical methods can be used to determine correlations, and analyze their applicability.

: http://publica.fraunhofer.de/dokumente/N-333095.html