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Capturing Dynamics of Mobile Context-Aware Systems with Rules and Statistical Analysis of Historical Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9120)

Abstract

Mobile context-aware systems gained huge popularity in recent years due to the rapid evolution of personal mobile devices. Nowadays smartphones are equipped with a variety of sensors that allow for on-line monitoring of user context and reasoning upon it. Contextual information in such systems is very dynamic. It changes rapidly and these changes may have impact on system behaviour. Although there are many machine learning methods like Markov models that allow to handle such dynamics, they do not provide intelligibility features that rule-based systems do. In this paper we propose an extension to XTT2 rule representation that allows for modelling dynamics of the mobile context-aware systems using rules and statistical analysis of historical data. This was achieved by introducing time-based operators to rule conditions and statistical operators to right hand side of the rules.

Keywords

Rule-based system Mobile computing Reasoning Statistics 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakowPoland

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