User-centric inference based on history of context data in pervasive environments

Authors:
Nikos Kalatzis;Ioanna Roussaki;Nicolas Liampotis;Maria Strimpakou;Carsten Pils
Affiliations:
National Technical University of Athens, Athens, Greece;National Technical University of Athens, Athens, Greece;National Technical University of Athens, Athens, Greece;National Technical University of Athens, Athens, Greece;Waterford Institute of Technology, Waterford, Ireland
Venue:
Proceedings of the 3rd international workshop on Services integration in pervasive environments
Year:
2008

Citing 5
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Abstract

Pervasive computing systems need to be strongly proactive. Context-awareness contributes to this, thus minimizing human-machine interaction. Context-aware systems are greatly enhanced by the utilization of recorded history of the users' situations and interactions. In this paper, an approach is proposed for modelling, storing and exploiting history-of-context, in order to predict or estimate context information. The proposed framework is context-type-independent, requires minimal processing and storage resources, and can be used for data compression. It is based on multiple context prediction rule generation models, demonstrates high prediction success ratio, and has been empirically evaluated via extensive experiments.