DocumentCode :
709148
Title :
Automatic derivation of context descriptions
Author :
Jung, Christian ; Feth, Denis ; Elrakaiby, Yehia
Author_Institution :
Fraunhofer Inst. for Exp. Software Eng. IESE, Kaiserslautern, Germany
fYear :
2015
fDate :
9-12 March 2015
Firstpage :
70
Lastpage :
76
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.
Keywords :
information systems; mobile computing; statistical analysis; context characterization; context description automatic derivation; context-awareness; contextual information; mobile information systems; statistical methods; Batteries; Context; Correlation; Logistics; Probes; Security; Sensors; Context description; Context-awareness; Mobile Devices; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2015 IEEE International Inter-Disciplinary Conference on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/COGSIMA.2015.7108177
Filename :
7108177
Link To Document :
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