A Context Quality Model to Support Transparent Reasoning with Uncertain Context

Susan McKeever, Juan Ye, Lorcan Coyle, Simon Dobson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)


Much research on context quality in context-aware systems divides into two strands: (1) the qualitative identification of quality measures and (2) the use of uncertain reasoning techniques. In this paper, we combine these two strands, exploring the problem of how to identify and propagate quality through the different context; layers in order to support the context reasoning process. We present a generalised, structured context quality model that supports aggregation of quality from sensor up to situation level. Our model supports reasoning processes that explicitly aggregate context quality, by enabling the identification and quantification of appropriate quality parameters. We demonstrate the efficacy of our model using an experimental sensor data set, gaining a significant improvement in situation recognition for our voting based reasoning algorithm.

Original languageEnglish
Title of host publicationQuality of Context: First International Workshop, QuaCon 2009, Stuttgart, Germany, June 25-26, 2009. Revised Papers
EditorsK. Rothermel, D. Fritsch, W. Blochinger, F. Dürr
Number of pages11
ISBN (Print)978-3-642-04558-5
Publication statusPublished - 2009
Event1st International Workshop on Quality of Context (QuaCon 2009) - Stuttgart, Germany
Duration: 25 Jun 200926 Jun 2009

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


Conference1st International Workshop on Quality of Context (QuaCon 2009)


  • Information
  • pervasive systems
  • ontologies,
  • uncertain reasoning
  • Clarity
  • Pudecas


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