A Context Quality Model to Support Transparent Reasoning with Uncertain Context

Much research on context quality in context-aware systems divides into two strands: (1) the qualitative identication 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 dierent 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 identication and quantication of appropriate quality parameters. We demonstrate the ecacy of our model using an experimental sensor data set, gaining a signicant improvement in situation recognition for our voting based reasoning algorithm.

• Type: Conference
• Year: 2009
• Where: QUACON
• Authors: Susan McKeever, Juan Ye, Lorcan Coyle, Simon Dobson
• Keywords: Context Quality, Context Quality Model, Information Management, QUACON 2009, Reasoning