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Issue No.06 - June (2012 vol.11)

pp: 1047-1059

Stephan Sigg , Technische Universitaet Braunschweig, Braunschweig

Dawud Gordon , Technische Universitaet Braunschweig, Braunschweig

Georg von Zengen , Technische Universitaet Braunschweig, Braunschweig

Michael Beigl , Technische Universitaet Braunschweig , Braunschweig

Sandra Haseloff , Kassel University, Kassel

Klaus David , Kassel University, Kassel

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2011.170

ABSTRACT

Context prediction is the task of inferring information about the progression of an observed context time series based on its previous behaviour. Prediction methods can be applied at several abstraction levels in the context processing chain. In a theoretical analysis as well as by means of experiments we show that the nature of the input data, the quality of the output, and finally the flow of processing operations used to make a prediction, are correlated. A comprehensive discussion of basic concepts in context prediction domains and a study on the effects of the context abstraction level on the context prediction accuracy in context prediction scenarios is provided. We develop a set of formulae that link scenario-dependent parameters to a probability for the context prediction accuracy. It is demonstrated that the results achieved in our theoretical analysis can also be confirmed in simulations as well as in experimental studies.

INDEX TERMS

Pervasive computing, stochastic processes, location-dependent and sensitive, performance evaluation of algorithms and systems, time series analysis.

CITATION

Stephan Sigg, Dawud Gordon, Georg von Zengen, Michael Beigl, Sandra Haseloff, Klaus David, "Investigation of Context Prediction Accuracy for Different Context Abstraction Levels",

*IEEE Transactions on Mobile Computing*, vol.11, no. 6, pp. 1047-1059, June 2012, doi:10.1109/TMC.2011.170REFERENCES